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File R-release.diff of Package R (Revision cb433469748e3af8ce1823a2fbae92ea)

Currently displaying revision cb433469748e3af8ce1823a2fbae92ea , Show latest

# cd *inside* the ...../R-4.3.2/  directory, and do
#      zcat ..../R-release.diff.gz | patch -p1 -E
# ---------                          =====
# You need a "g[un]zip capable zcat", and canNOT use Solaris "patch"!
# Rather get ("gzip" and)  "diffutils" from any GNU mirror.
#
diff -ru -P -x .mirror -x ls_lR -x Old R-release-orig/SVN-REVISION R-patched/SVN-REVISION
--- R-release-orig/SVN-REVISION	2023-10-31 09:02:29.000000000 +0100
+++ R-patched/SVN-REVISION	2024-02-11 01:32:17.058738172 +0100
@@ -1,2 +1,2 @@
-Revision: 85441
-Last Changed Date: 2023-10-31
+Revision: 85885
+Last Changed Date: 2024-02-08
diff -ru -P -x .mirror -x ls_lR -x Old R-release-orig/VERSION R-patched/VERSION
--- R-release-orig/VERSION	2023-10-31 09:00:02.000000000 +0100
+++ R-patched/VERSION	2023-10-31 17:45:08.002681770 +0100
@@ -1 +1 @@
-4.3.2
+4.3.2 Patched
diff -ru -P -x .mirror -x ls_lR -x Old R-release-orig/config.site R-patched/config.site
--- R-release-orig/config.site	2023-03-24 00:02:02.000000000 +0100
+++ R-patched/config.site	2024-02-02 01:31:08.558482565 +0100
@@ -43,7 +43,7 @@
 ## To override this choice, specify the name or path of the command
 ## which runs the compiler, for example 'c99'.
 ## It is also necessary to set the architecture here, e.g. 'gcc -m32'.
-## If this is a wrappwr it should pass on --version to the real compiler.
+## If this is a wrapper it should pass on --version to the real compiler.
 ## CC=
 
 ## Debugging and optimization options for the C compiler.
@@ -103,7 +103,7 @@
 
 ## The command which runs the Fortran compiler.
 ## Used for both fixed-form and free-form Fortran
-## If this is a wrappwr it should pass on --version to the real compiler.
+## If this is a wrapper it should pass on --version to the real compiler.
 ## FC=
 
 ## Options for the Fortran compiler.
@@ -206,7 +206,7 @@
 ## uses the values of the environment variables 'CXX' or 'CCC' if set,
 ## and then looks under the names 'c++', 'g++', 'CC' and more OS-specific
 ## names (from autoconf).
-## If this is a wrappwr it should pass on --version to the real compiler.
+## If this is a wrapper it should pass on --version to the real compiler.
 ## CXX=
 
 ## Options for the C++ compiler.
@@ -218,7 +218,7 @@
 ## CXXPICFLAGS=
 
 ## Option to specify the default C++ standard, 
-## e.g. -std=c++11 or -std=gnu++11
+## e.g. -std=c++14 or -std=gnu++14
 ## CXXSTD=
 
 ## The command to be used to load shared objects which contain object
diff -ru -P -x .mirror -x ls_lR -x Old R-release-orig/configure R-patched/configure
--- R-release-orig/configure	2023-10-31 09:01:22.000000000 +0100
+++ R-patched/configure	2024-01-03 17:45:07.604617012 +0100
@@ -183,7 +183,6 @@
   as_lineno_2=";as_suggested=$as_suggested$LINENO;as_suggested=$as_suggested" as_lineno_2a=\$LINENO
   eval 'test \"x\$as_lineno_1'\$as_run'\" != \"x\$as_lineno_2'\$as_run'\" &&
   test \"x\`expr \$as_lineno_1'\$as_run' + 1\`\" = \"x\$as_lineno_2'\$as_run'\"' || exit 1
-test \$(( 1 + 1 )) = 2 || exit 1
 
   test -n \"\${ZSH_VERSION+set}\${BASH_VERSION+set}\" || (
     ECHO='\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\'
@@ -191,7 +190,8 @@
     ECHO=\$ECHO\$ECHO\$ECHO\$ECHO\$ECHO\$ECHO
     PATH=/empty FPATH=/empty; export PATH FPATH
     test \"X\`printf %s \$ECHO\`\" = \"X\$ECHO\" \\
-      || test \"X\`print -r -- \$ECHO\`\" = \"X\$ECHO\" ) || exit 1"
+      || test \"X\`print -r -- \$ECHO\`\" = \"X\$ECHO\" ) || exit 1
+test \$(( 1 + 1 )) = 2 || exit 1"
   if (eval "$as_required") 2>/dev/null
 then :
   as_have_required=yes
@@ -881,6 +881,8 @@
 DUMPBIN
 LD
 FGREP
+EGREP
+GREP
 LIBTOOL
 C99FLAGS
 CC99
@@ -906,8 +908,6 @@
 ac_ct_FC
 FCFLAGS
 FC
-EGREP
-GREP
 CPP
 OBJEXT
 EXEEXT
@@ -2196,6 +2196,39 @@
 
 } # ac_fn_c_try_compile
 
+# ac_fn_c_check_header_compile LINENO HEADER VAR INCLUDES
+# -------------------------------------------------------
+# Tests whether HEADER exists and can be compiled using the include files in
+# INCLUDES, setting the cache variable VAR accordingly.
+ac_fn_c_check_header_compile ()
+{
+  as_lineno=${as_lineno-"$1"} as_lineno_stack=as_lineno_stack=$as_lineno_stack
+  { printf "%s\n" "$as_me:${as_lineno-$LINENO}: checking for $2" >&5
+printf %s "checking for $2... " >&6; }
+if eval test \${$3+y}
+then :
+  printf %s "(cached) " >&6
+else $as_nop
+  cat confdefs.h - <<_ACEOF >conftest.$ac_ext
+/* end confdefs.h.  */
+$4
+#include <$2>
+_ACEOF
+if ac_fn_c_try_compile "$LINENO"
+then :
+  eval "$3=yes"
+else $as_nop
+  eval "$3=no"
+fi
+rm -f core conftest.err conftest.$ac_objext conftest.beam conftest.$ac_ext
+fi
+eval ac_res=\$$3
+	       { printf "%s\n" "$as_me:${as_lineno-$LINENO}: result: $ac_res" >&5
+printf "%s\n" "$ac_res" >&6; }
+  eval $as_lineno_stack; ${as_lineno_stack:+:} unset as_lineno
+
+} # ac_fn_c_check_header_compile
+
 # ac_fn_c_try_cpp LINENO
 # ----------------------
 # Try to preprocess conftest.$ac_ext, and return whether this succeeded.
@@ -2234,39 +2267,6 @@
 
 } # ac_fn_c_try_cpp
 
-# ac_fn_c_check_header_compile LINENO HEADER VAR INCLUDES
-# -------------------------------------------------------
-# Tests whether HEADER exists and can be compiled using the include files in
-# INCLUDES, setting the cache variable VAR accordingly.
-ac_fn_c_check_header_compile ()
-{
-  as_lineno=${as_lineno-"$1"} as_lineno_stack=as_lineno_stack=$as_lineno_stack
-  { printf "%s\n" "$as_me:${as_lineno-$LINENO}: checking for $2" >&5
-printf %s "checking for $2... " >&6; }
-if eval test \${$3+y}
-then :
-  printf %s "(cached) " >&6
-else $as_nop
-  cat confdefs.h - <<_ACEOF >conftest.$ac_ext
-/* end confdefs.h.  */
-$4
-#include <$2>
-_ACEOF
-if ac_fn_c_try_compile "$LINENO"
-then :
-  eval "$3=yes"
-else $as_nop
-  eval "$3=no"
-fi
-rm -f core conftest.err conftest.$ac_objext conftest.beam conftest.$ac_ext
-fi
-eval ac_res=\$$3
-	       { printf "%s\n" "$as_me:${as_lineno-$LINENO}: result: $ac_res" >&5
-printf "%s\n" "$ac_res" >&6; }
-  eval $as_lineno_stack; ${as_lineno_stack:+:} unset as_lineno
-
-} # ac_fn_c_check_header_compile
-
 # ac_fn_fc_try_compile LINENO
 # ---------------------------
 # Try to compile conftest.$ac_ext, and return whether this succeeded.
@@ -7677,326 +7677,6 @@
 ac_compiler_gnu=$ac_cv_c_compiler_gnu
 
 
-ac_ext=c
-ac_cpp='$CPP $CPPFLAGS'
-ac_compile='$CC -c $CFLAGS $CPPFLAGS conftest.$ac_ext >&5'
-ac_link='$CC -o conftest$ac_exeext $CFLAGS $CPPFLAGS $LDFLAGS conftest.$ac_ext $LIBS >&5'
-ac_compiler_gnu=$ac_cv_c_compiler_gnu
-{ printf "%s\n" "$as_me:${as_lineno-$LINENO}: checking how to run the C preprocessor" >&5
-printf %s "checking how to run the C preprocessor... " >&6; }
-# On Suns, sometimes $CPP names a directory.
-if test -n "$CPP" && test -d "$CPP"; then
-  CPP=
-fi
-if test -z "$CPP"; then
-  if test ${ac_cv_prog_CPP+y}
-then :
-  printf %s "(cached) " >&6
-else $as_nop
-      # Double quotes because $CC needs to be expanded
-    for CPP in "$CC -E" "$CC -E -traditional-cpp" cpp /lib/cpp
-    do
-      ac_preproc_ok=false
-for ac_c_preproc_warn_flag in '' yes
-do
-  # Use a header file that comes with gcc, so configuring glibc
-  # with a fresh cross-compiler works.
-  # On the NeXT, cc -E runs the code through the compiler's parser,
-  # not just through cpp. "Syntax error" is here to catch this case.
-  cat confdefs.h - <<_ACEOF >conftest.$ac_ext
-/* end confdefs.h.  */
-#include <limits.h>
-		     Syntax error
-_ACEOF
-if ac_fn_c_try_cpp "$LINENO"
-then :
-
-else $as_nop
-  # Broken: fails on valid input.
-continue
-fi
-rm -f conftest.err conftest.i conftest.$ac_ext
-
-  # OK, works on sane cases.  Now check whether nonexistent headers
-  # can be detected and how.
-  cat confdefs.h - <<_ACEOF >conftest.$ac_ext
-/* end confdefs.h.  */
-#include <ac_nonexistent.h>
-_ACEOF
-if ac_fn_c_try_cpp "$LINENO"
-then :
-  # Broken: success on invalid input.
-continue
-else $as_nop
-  # Passes both tests.
-ac_preproc_ok=:
-break
-fi
-rm -f conftest.err conftest.i conftest.$ac_ext
-
-done
-# Because of `break', _AC_PREPROC_IFELSE's cleaning code was skipped.
-rm -f conftest.i conftest.err conftest.$ac_ext
-if $ac_preproc_ok
-then :
-  break
-fi
-
-    done
-    ac_cv_prog_CPP=$CPP
-
-fi
-  CPP=$ac_cv_prog_CPP
-else
-  ac_cv_prog_CPP=$CPP
-fi
-{ printf "%s\n" "$as_me:${as_lineno-$LINENO}: result: $CPP" >&5
-printf "%s\n" "$CPP" >&6; }
-ac_preproc_ok=false
-for ac_c_preproc_warn_flag in '' yes
-do
-  # Use a header file that comes with gcc, so configuring glibc
-  # with a fresh cross-compiler works.
-  # On the NeXT, cc -E runs the code through the compiler's parser,
-  # not just through cpp. "Syntax error" is here to catch this case.
-  cat confdefs.h - <<_ACEOF >conftest.$ac_ext
-/* end confdefs.h.  */
-#include <limits.h>
-		     Syntax error
-_ACEOF
-if ac_fn_c_try_cpp "$LINENO"
-then :
-
-else $as_nop
-  # Broken: fails on valid input.
-continue
-fi
-rm -f conftest.err conftest.i conftest.$ac_ext
-
-  # OK, works on sane cases.  Now check whether nonexistent headers
-  # can be detected and how.
-  cat confdefs.h - <<_ACEOF >conftest.$ac_ext
-/* end confdefs.h.  */
-#include <ac_nonexistent.h>
-_ACEOF
-if ac_fn_c_try_cpp "$LINENO"
-then :
-  # Broken: success on invalid input.
-continue
-else $as_nop
-  # Passes both tests.
-ac_preproc_ok=:
-break
-fi
-rm -f conftest.err conftest.i conftest.$ac_ext
-
-done
-# Because of `break', _AC_PREPROC_IFELSE's cleaning code was skipped.
-rm -f conftest.i conftest.err conftest.$ac_ext
-if $ac_preproc_ok
-then :
-
-else $as_nop
-  { { printf "%s\n" "$as_me:${as_lineno-$LINENO}: error: in \`$ac_pwd':" >&5
-printf "%s\n" "$as_me: error: in \`$ac_pwd':" >&2;}
-as_fn_error $? "C preprocessor \"$CPP\" fails sanity check
-See \`config.log' for more details" "$LINENO" 5; }
-fi
-
-ac_ext=c
-ac_cpp='$CPP $CPPFLAGS'
-ac_compile='$CC -c $CFLAGS $CPPFLAGS conftest.$ac_ext >&5'
-ac_link='$CC -o conftest$ac_exeext $CFLAGS $CPPFLAGS $LDFLAGS conftest.$ac_ext $LIBS >&5'
-ac_compiler_gnu=$ac_cv_c_compiler_gnu
-
-
-{ printf "%s\n" "$as_me:${as_lineno-$LINENO}: checking for grep that handles long lines and -e" >&5
-printf %s "checking for grep that handles long lines and -e... " >&6; }
-if test ${ac_cv_path_GREP+y}
-then :
-  printf %s "(cached) " >&6
-else $as_nop
-  if test -z "$GREP"; then
-  ac_path_GREP_found=false
-  # Loop through the user's path and test for each of PROGNAME-LIST
-  as_save_IFS=$IFS; IFS=$PATH_SEPARATOR
-for as_dir in $PATH$PATH_SEPARATOR/usr/xpg4/bin
-do
-  IFS=$as_save_IFS
-  case $as_dir in #(((
-    '') as_dir=./ ;;
-    */) ;;
-    *) as_dir=$as_dir/ ;;
-  esac
-    for ac_prog in grep ggrep
-   do
-    for ac_exec_ext in '' $ac_executable_extensions; do
-      ac_path_GREP="$as_dir$ac_prog$ac_exec_ext"
-      as_fn_executable_p "$ac_path_GREP" || continue
-# Check for GNU ac_path_GREP and select it if it is found.
-  # Check for GNU $ac_path_GREP
-case `"$ac_path_GREP" --version 2>&1` in
-*GNU*)
-  ac_cv_path_GREP="$ac_path_GREP" ac_path_GREP_found=:;;
-*)
-  ac_count=0
-  printf %s 0123456789 >"conftest.in"
-  while :
-  do
-    cat "conftest.in" "conftest.in" >"conftest.tmp"
-    mv "conftest.tmp" "conftest.in"
-    cp "conftest.in" "conftest.nl"
-    printf "%s\n" 'GREP' >> "conftest.nl"
-    "$ac_path_GREP" -e 'GREP$' -e '-(cannot match)-' < "conftest.nl" >"conftest.out" 2>/dev/null || break
-    diff "conftest.out" "conftest.nl" >/dev/null 2>&1 || break
-    as_fn_arith $ac_count + 1 && ac_count=$as_val
-    if test $ac_count -gt ${ac_path_GREP_max-0}; then
-      # Best one so far, save it but keep looking for a better one
-      ac_cv_path_GREP="$ac_path_GREP"
-      ac_path_GREP_max=$ac_count
-    fi
-    # 10*(2^10) chars as input seems more than enough
-    test $ac_count -gt 10 && break
-  done
-  rm -f conftest.in conftest.tmp conftest.nl conftest.out;;
-esac
-
-      $ac_path_GREP_found && break 3
-    done
-  done
-  done
-IFS=$as_save_IFS
-  if test -z "$ac_cv_path_GREP"; then
-    as_fn_error $? "no acceptable grep could be found in $PATH$PATH_SEPARATOR/usr/xpg4/bin" "$LINENO" 5
-  fi
-else
-  ac_cv_path_GREP=$GREP
-fi
-
-fi
-{ printf "%s\n" "$as_me:${as_lineno-$LINENO}: result: $ac_cv_path_GREP" >&5
-printf "%s\n" "$ac_cv_path_GREP" >&6; }
- GREP="$ac_cv_path_GREP"
-
-
-{ printf "%s\n" "$as_me:${as_lineno-$LINENO}: checking for egrep" >&5
-printf %s "checking for egrep... " >&6; }
-if test ${ac_cv_path_EGREP+y}
-then :
-  printf %s "(cached) " >&6
-else $as_nop
-  if echo a | $GREP -E '(a|b)' >/dev/null 2>&1
-   then ac_cv_path_EGREP="$GREP -E"
-   else
-     if test -z "$EGREP"; then
-  ac_path_EGREP_found=false
-  # Loop through the user's path and test for each of PROGNAME-LIST
-  as_save_IFS=$IFS; IFS=$PATH_SEPARATOR
-for as_dir in $PATH$PATH_SEPARATOR/usr/xpg4/bin
-do
-  IFS=$as_save_IFS
-  case $as_dir in #(((
-    '') as_dir=./ ;;
-    */) ;;
-    *) as_dir=$as_dir/ ;;
-  esac
-    for ac_prog in egrep
-   do
-    for ac_exec_ext in '' $ac_executable_extensions; do
-      ac_path_EGREP="$as_dir$ac_prog$ac_exec_ext"
-      as_fn_executable_p "$ac_path_EGREP" || continue
-# Check for GNU ac_path_EGREP and select it if it is found.
-  # Check for GNU $ac_path_EGREP
-case `"$ac_path_EGREP" --version 2>&1` in
-*GNU*)
-  ac_cv_path_EGREP="$ac_path_EGREP" ac_path_EGREP_found=:;;
-*)
-  ac_count=0
-  printf %s 0123456789 >"conftest.in"
-  while :
-  do
-    cat "conftest.in" "conftest.in" >"conftest.tmp"
-    mv "conftest.tmp" "conftest.in"
-    cp "conftest.in" "conftest.nl"
-    printf "%s\n" 'EGREP' >> "conftest.nl"
-    "$ac_path_EGREP" 'EGREP$' < "conftest.nl" >"conftest.out" 2>/dev/null || break
-    diff "conftest.out" "conftest.nl" >/dev/null 2>&1 || break
-    as_fn_arith $ac_count + 1 && ac_count=$as_val
-    if test $ac_count -gt ${ac_path_EGREP_max-0}; then
-      # Best one so far, save it but keep looking for a better one
-      ac_cv_path_EGREP="$ac_path_EGREP"
-      ac_path_EGREP_max=$ac_count
-    fi
-    # 10*(2^10) chars as input seems more than enough
-    test $ac_count -gt 10 && break
-  done
-  rm -f conftest.in conftest.tmp conftest.nl conftest.out;;
-esac
-
-      $ac_path_EGREP_found && break 3
-    done
-  done
-  done
-IFS=$as_save_IFS
-  if test -z "$ac_cv_path_EGREP"; then
-    as_fn_error $? "no acceptable egrep could be found in $PATH$PATH_SEPARATOR/usr/xpg4/bin" "$LINENO" 5
-  fi
-else
-  ac_cv_path_EGREP=$EGREP
-fi
-
-   fi
-fi
-{ printf "%s\n" "$as_me:${as_lineno-$LINENO}: result: $ac_cv_path_EGREP" >&5
-printf "%s\n" "$ac_cv_path_EGREP" >&6; }
- EGREP="$ac_cv_path_EGREP"
-
-
-if test $ac_cv_c_compiler_gnu = yes; then
-    { printf "%s\n" "$as_me:${as_lineno-$LINENO}: checking whether $CC needs -traditional" >&5
-printf %s "checking whether $CC needs -traditional... " >&6; }
-if test ${ac_cv_prog_gcc_traditional+y}
-then :
-  printf %s "(cached) " >&6
-else $as_nop
-    ac_pattern="Autoconf.*'x'"
-  cat confdefs.h - <<_ACEOF >conftest.$ac_ext
-/* end confdefs.h.  */
-#include <sgtty.h>
-Autoconf TIOCGETP
-_ACEOF
-if (eval "$ac_cpp conftest.$ac_ext") 2>&5 |
-  $EGREP "$ac_pattern" >/dev/null 2>&1
-then :
-  ac_cv_prog_gcc_traditional=yes
-else $as_nop
-  ac_cv_prog_gcc_traditional=no
-fi
-rm -rf conftest*
-
-
-  if test $ac_cv_prog_gcc_traditional = no; then
-    cat confdefs.h - <<_ACEOF >conftest.$ac_ext
-/* end confdefs.h.  */
-#include <termio.h>
-Autoconf TCGETA
-_ACEOF
-if (eval "$ac_cpp conftest.$ac_ext") 2>&5 |
-  $EGREP "$ac_pattern" >/dev/null 2>&1
-then :
-  ac_cv_prog_gcc_traditional=yes
-fi
-rm -rf conftest*
-
-  fi
-fi
-{ printf "%s\n" "$as_me:${as_lineno-$LINENO}: result: $ac_cv_prog_gcc_traditional" >&5
-printf "%s\n" "$ac_cv_prog_gcc_traditional" >&6; }
-  if test $ac_cv_prog_gcc_traditional = yes; then
-    CC="$CC -traditional"
-  fi
-fi
-
 ac_header= ac_cache=
 for ac_item in $ac_header_c_list
 do
@@ -10348,6 +10028,148 @@
 
 
 
+{ printf "%s\n" "$as_me:${as_lineno-$LINENO}: checking for grep that handles long lines and -e" >&5
+printf %s "checking for grep that handles long lines and -e... " >&6; }
+if test ${ac_cv_path_GREP+y}
+then :
+  printf %s "(cached) " >&6
+else $as_nop
+  if test -z "$GREP"; then
+  ac_path_GREP_found=false
+  # Loop through the user's path and test for each of PROGNAME-LIST
+  as_save_IFS=$IFS; IFS=$PATH_SEPARATOR
+for as_dir in $PATH$PATH_SEPARATOR/usr/xpg4/bin
+do
+  IFS=$as_save_IFS
+  case $as_dir in #(((
+    '') as_dir=./ ;;
+    */) ;;
+    *) as_dir=$as_dir/ ;;
+  esac
+    for ac_prog in grep ggrep
+   do
+    for ac_exec_ext in '' $ac_executable_extensions; do
+      ac_path_GREP="$as_dir$ac_prog$ac_exec_ext"
+      as_fn_executable_p "$ac_path_GREP" || continue
+# Check for GNU ac_path_GREP and select it if it is found.
+  # Check for GNU $ac_path_GREP
+case `"$ac_path_GREP" --version 2>&1` in
+*GNU*)
+  ac_cv_path_GREP="$ac_path_GREP" ac_path_GREP_found=:;;
+*)
+  ac_count=0
+  printf %s 0123456789 >"conftest.in"
+  while :
+  do
+    cat "conftest.in" "conftest.in" >"conftest.tmp"
+    mv "conftest.tmp" "conftest.in"
+    cp "conftest.in" "conftest.nl"
+    printf "%s\n" 'GREP' >> "conftest.nl"
+    "$ac_path_GREP" -e 'GREP$' -e '-(cannot match)-' < "conftest.nl" >"conftest.out" 2>/dev/null || break
+    diff "conftest.out" "conftest.nl" >/dev/null 2>&1 || break
+    as_fn_arith $ac_count + 1 && ac_count=$as_val
+    if test $ac_count -gt ${ac_path_GREP_max-0}; then
+      # Best one so far, save it but keep looking for a better one
+      ac_cv_path_GREP="$ac_path_GREP"
+      ac_path_GREP_max=$ac_count
+    fi
+    # 10*(2^10) chars as input seems more than enough
+    test $ac_count -gt 10 && break
+  done
+  rm -f conftest.in conftest.tmp conftest.nl conftest.out;;
+esac
+
+      $ac_path_GREP_found && break 3
+    done
+  done
+  done
+IFS=$as_save_IFS
+  if test -z "$ac_cv_path_GREP"; then
+    as_fn_error $? "no acceptable grep could be found in $PATH$PATH_SEPARATOR/usr/xpg4/bin" "$LINENO" 5
+  fi
+else
+  ac_cv_path_GREP=$GREP
+fi
+
+fi
+{ printf "%s\n" "$as_me:${as_lineno-$LINENO}: result: $ac_cv_path_GREP" >&5
+printf "%s\n" "$ac_cv_path_GREP" >&6; }
+ GREP="$ac_cv_path_GREP"
+
+
+{ printf "%s\n" "$as_me:${as_lineno-$LINENO}: checking for egrep" >&5
+printf %s "checking for egrep... " >&6; }
+if test ${ac_cv_path_EGREP+y}
+then :
+  printf %s "(cached) " >&6
+else $as_nop
+  if echo a | $GREP -E '(a|b)' >/dev/null 2>&1
+   then ac_cv_path_EGREP="$GREP -E"
+   else
+     if test -z "$EGREP"; then
+  ac_path_EGREP_found=false
+  # Loop through the user's path and test for each of PROGNAME-LIST
+  as_save_IFS=$IFS; IFS=$PATH_SEPARATOR
+for as_dir in $PATH$PATH_SEPARATOR/usr/xpg4/bin
+do
+  IFS=$as_save_IFS
+  case $as_dir in #(((
+    '') as_dir=./ ;;
+    */) ;;
+    *) as_dir=$as_dir/ ;;
+  esac
+    for ac_prog in egrep
+   do
+    for ac_exec_ext in '' $ac_executable_extensions; do
+      ac_path_EGREP="$as_dir$ac_prog$ac_exec_ext"
+      as_fn_executable_p "$ac_path_EGREP" || continue
+# Check for GNU ac_path_EGREP and select it if it is found.
+  # Check for GNU $ac_path_EGREP
+case `"$ac_path_EGREP" --version 2>&1` in
+*GNU*)
+  ac_cv_path_EGREP="$ac_path_EGREP" ac_path_EGREP_found=:;;
+*)
+  ac_count=0
+  printf %s 0123456789 >"conftest.in"
+  while :
+  do
+    cat "conftest.in" "conftest.in" >"conftest.tmp"
+    mv "conftest.tmp" "conftest.in"
+    cp "conftest.in" "conftest.nl"
+    printf "%s\n" 'EGREP' >> "conftest.nl"
+    "$ac_path_EGREP" 'EGREP$' < "conftest.nl" >"conftest.out" 2>/dev/null || break
+    diff "conftest.out" "conftest.nl" >/dev/null 2>&1 || break
+    as_fn_arith $ac_count + 1 && ac_count=$as_val
+    if test $ac_count -gt ${ac_path_EGREP_max-0}; then
+      # Best one so far, save it but keep looking for a better one
+      ac_cv_path_EGREP="$ac_path_EGREP"
+      ac_path_EGREP_max=$ac_count
+    fi
+    # 10*(2^10) chars as input seems more than enough
+    test $ac_count -gt 10 && break
+  done
+  rm -f conftest.in conftest.tmp conftest.nl conftest.out;;
+esac
+
+      $ac_path_EGREP_found && break 3
+    done
+  done
+  done
+IFS=$as_save_IFS
+  if test -z "$ac_cv_path_EGREP"; then
+    as_fn_error $? "no acceptable egrep could be found in $PATH$PATH_SEPARATOR/usr/xpg4/bin" "$LINENO" 5
+  fi
+else
+  ac_cv_path_EGREP=$EGREP
+fi
+
+   fi
+fi
+{ printf "%s\n" "$as_me:${as_lineno-$LINENO}: result: $ac_cv_path_EGREP" >&5
+printf "%s\n" "$ac_cv_path_EGREP" >&6; }
+ EGREP="$ac_cv_path_EGREP"
+
+
 { printf "%s\n" "$as_me:${as_lineno-$LINENO}: checking for fgrep" >&5
 printf %s "checking for fgrep... " >&6; }
 if test ${ac_cv_path_FGREP+y}
@@ -25614,6 +25436,7 @@
 
 fi
 
+
 { printf "%s\n" "$as_me:${as_lineno-$LINENO}: checking for GNU C library with version >= 2" >&5
 printf %s "checking for GNU C library with version >= 2... " >&6; }
 if test ${r_cv_header_glibc2+y}
@@ -27060,7 +26883,7 @@
 # flags.
 r_save_CFLAGS=$CFLAGS
 CFLAGS="$CFLAGS $r_verb"
-(eval echo $as_me:27065: \"$ac_link\") >&5
+(eval echo $as_me:26888: \"$ac_link\") >&5
 r_c_v_output=`eval $ac_link 5>&1 2>&1 | grep -v 'Driving:'`
 echo "$r_c_v_output" >&5
 CFLAGS=$r_save_CFLAGS
@@ -27136,7 +26959,7 @@
 # flags.
 r_save_CFLAGS=$CFLAGS
 CFLAGS="$CFLAGS $r_cv_prog_c_v"
-(eval echo $as_me:27141: \"$ac_link\") >&5
+(eval echo $as_me:26964: \"$ac_link\") >&5
 r_c_v_output=`eval $ac_link 5>&1 2>&1 | grep -v 'Driving:'`
 echo "$r_c_v_output" >&5
 CFLAGS=$r_save_CFLAGS
diff -ru -P -x .mirror -x ls_lR -x Old R-release-orig/configure.ac R-patched/configure.ac
--- R-release-orig/configure.ac	2023-08-03 00:15:02.000000000 +0200
+++ R-patched/configure.ac	2024-01-03 17:45:07.658164022 +0100
@@ -20,7 +20,7 @@
 ### along with R; if not, a copy is available at
 ### https://www.r-project.org/Licenses/
 
-AC_PREREQ(2.69)
+AC_PREREQ([2.69])
 
 ## We want to get the version number from file 'VERSION' (rather than
 ## specifying the version info in 'configure.ac'.  Hence, we need a bit
@@ -740,8 +740,7 @@
 AC_ARG_VAR([PKG_CONFIG_LIBDIR], [path overriding pkg-config's default search path])
 
 AC_PROG_CC
-AC_PROG_GCC_TRADITIONAL
-dnl AC_GNU_SOURCE ## see note above
+dnl AC_PROG_GCC_TRADITIONAL
 AC_USE_SYSTEM_EXTENSIONS ## see note above
 
 AC_PROG_CPP
diff -ru -P -x .mirror -x ls_lR -x Old R-release-orig/doc/FAQ R-patched/doc/FAQ
--- R-release-orig/doc/FAQ	2023-10-31 09:02:29.000000000 +0100
+++ R-patched/doc/FAQ	2024-02-11 01:32:16.630818066 +0100
@@ -86,7 +86,7 @@
   7.28 Why is read.table() so inefficient?
   7.29 What is the difference between package and library?
   7.30 I installed a package but the functions are not there
-  7.31 Why doesn't R think these numbers are equal?
+  7.31 Why doesn’t R think these numbers are equal?
   7.32 How can I capture or ignore errors in a long simulation?
   7.33 Why are powers of negative numbers wrong?
   7.34 How can I save the result of each iteration in a loop into a separate file?
@@ -122,8 +122,8 @@
 1.1 Legalese
 ============
 
-Copyright (C) 1998-2020 Kurt Hornik
-Copyright (C) 2021-2023 R Core Team
+Copyright © 1998–2020 Kurt Hornik
+Copyright © 2021–2023 R Core Team
 
    This document is free software; you can redistribute it and/or modify it
 under the terms of the GNU General Public License as published by the Free
@@ -150,14 +150,14 @@
 info, HTML, PDF, as well as the Texinfo source used for creating all these
 formats using the GNU Texinfo system.
 
-   You can also obtain the R FAQ from the 'doc/FAQ' subdirectory of a CRAN
+   You can also obtain the R FAQ from the ‘doc/FAQ’ subdirectory of a CRAN
 site (*note What is CRAN?::).
 
 1.3 Citing this document
 ========================
 
 In publications, please refer to this FAQ as Hornik and R Core Team (2023),
-"The R FAQ", and give the above, _official_ URL:
+“The R FAQ”, and give the above, _official_ URL:
 
      @Misc{,
        author        = {Kurt Hornik and the R Core Team},
@@ -169,8 +169,8 @@
 1.4 Notation
 ============
 
-Everything should be pretty standard.  'R>' is used for the R prompt, and a
-'$' for the shell prompt (where applicable).
+Everything should be pretty standard.  ‘R>’ is used for the R prompt, and a
+‘$’ for the shell prompt (where applicable).
 
 1.5 Feedback
 ============
@@ -178,9 +178,9 @@
 Feedback via email to <R-devel@R-project.org> is most welcome.
 
    Features specific to the Windows and macOS ports of R are described in
-the "R for Windows FAQ"
-(https://CRAN.R-project.org/bin/windows/base/rw-FAQ.html) and the "R for Mac
-OS X FAQ" (https://CRAN.R-project.org/bin/macosx/RMacOSX-FAQ.html).  If you
+the “R for Windows FAQ”
+(https://CRAN.R-project.org/bin/windows/base/rw-FAQ.html) and the “R for Mac
+OS X FAQ” (https://CRAN.R-project.org/bin/macosx/RMacOSX-FAQ.html).  If you
 have information on Mac or Windows systems that you think should be added to
 this document, please let us know.
 
@@ -196,7 +196,7 @@
 files.
 
    The design of R has been heavily influenced by two existing languages:
-Becker, Chambers & Wilks' S (*note What is S?::) and Sussman's Scheme
+Becker, Chambers & Wilks’ S (*note What is S?::) and Sussman’s Scheme
 (http://community.schemewiki.org/?scheme-faq).  Whereas the resulting
 language is very similar in appearance to S, the underlying implementation
 and semantics are derived from Scheme.  *Note What are the differences
@@ -211,8 +211,8 @@
 models, nonlinear regression models, time series analysis, classical
 parametric and nonparametric tests, clustering and smoothing.  There is also
 a large set of functions which provide a flexible graphical environment for
-creating various kinds of data presentations.  Additional modules ("add-on
-packages") are available for a variety of specific purposes (*note R Add-On
+creating various kinds of data presentations.  Additional modules (“add-on
+packages”) are available for a variety of specific purposes (*note R Add-On
 Packages::).
 
    R was initially written by Ross Ihaka <Ross.Ihaka@R-project.org> and
@@ -221,7 +221,7 @@
 addition, a large group of individuals has contributed to R by sending code
 and bug reports.
 
-   Since mid-1997 there has been a core group (the "R Core Team") who can
+   Since mid-1997 there has been a core group (the “R Core Team”) who can
 modify the R source code archive.  The group currently consists of Doug
 Bates, John Chambers, Peter Dalgaard, Robert Gentleman, Kurt Hornik, Ross
 Ihaka, Tomas Kalibera, Michael Lawrence, Friedrich Leisch, Uwe Ligges,
@@ -232,7 +232,7 @@
    R has a home page at <https://www.R-project.org/>.  It is free software
 (https://www.gnu.org/philosophy/free-sw.html) distributed under a GNU-style
 copyleft (https://www.gnu.org/copyleft/copyleft.html), and an official part
-of the GNU (https://www.gnu.org/) project ("GNU S").
+of the GNU (https://www.gnu.org/) project (“GNU S”).
 
 2.2 What machines does R run on?
 ================================
@@ -254,11 +254,11 @@
 2.3 What is the current version of R?
 =====================================
 
-R uses a 'major.minor.patchlevel' numbering scheme.  Based on this, there
-are the current release version of R ('r-release') as well as two
+R uses a ‘major.minor.patchlevel’ numbering scheme.  Based on this, there
+are the current release version of R (‘r-release’) as well as two
 development versions of R, a patched version of the current release
-('r-patched') and one working towards the next minor or eventually major
-('r-devel') releases of R, respectively.  New features are typically
+(‘r-patched’) and one working towards the next minor or eventually major
+(‘r-devel’) releases of R, respectively.  New features are typically
 introduced in r-devel, while r-patched is for bug fixes mostly.
 
    See <https://CRAN.R-project.org/sources.html> for the current versions of
@@ -268,7 +268,7 @@
 ==========================
 
 Sources, binaries and documentation for R can be obtained via CRAN, the
-"Comprehensive R Archive Network" (see *note What is CRAN?::).
+“Comprehensive R Archive Network” (see *note What is CRAN?::).
 
    Sources are also available via <https://svn.R-project.org/R/>, the R
 Subversion repository, but currently not via anonymous rsync (nor CVS).
@@ -282,7 +282,7 @@
 2.5.1 How can R be installed (Unix-like)
 ----------------------------------------
 
-If R is already installed, it can be started by typing 'R' at the shell
+If R is already installed, it can be started by typing ‘R’ at the shell
 prompt (of course, provided that the executable is in your path).
 
    If binaries are available for your platform (see *note Are there
@@ -291,8 +291,8 @@
 
    Otherwise, you can compile and install R yourself, which can be done very
 easily under a number of common Unix-like platforms (see *note What machines
-does R run on?::).  The file 'INSTALL' that comes with the R distribution
-contains a brief introduction, and the "R Installation and Administration"
+does R run on?::).  The file ‘INSTALL’ that comes with the R distribution
+contains a brief introduction, and the “R Installation and Administration”
 guide (*note What documentation exists for R?::) has full details.
 
    Note that you need a FORTRAN 90 compiler as well as a C compiler to build
@@ -305,48 +305,48 @@
      $ make
 
    If these commands execute successfully, the R binary and a shell script
-front-end called 'R' are created and copied to the 'bin' directory.  You can
+front-end called ‘R’ are created and copied to the ‘bin’ directory.  You can
 copy the script to a place where users can invoke it, for example to
-'/usr/local/bin'.  In addition, HTML versions of the R manuals (e.g.,
-'R-exts.html', the "Writing R Extensions" manual) are built in the
-'doc/manual' subdirectory.
+‘/usr/local/bin’.  In addition, HTML versions of the R manuals (e.g.,
+‘R-exts.html’, the “Writing R Extensions” manual) are built in the
+‘doc/manual’ subdirectory.
 
-   Use 'make pdf' to build PDF (Portable Document Format) versions of the R
-manuals, including 'fullrefman.pdf' (an R object reference index).  Manuals
+   Use ‘make pdf’ to build PDF (Portable Document Format) versions of the R
+manuals, including ‘fullrefman.pdf’ (an R object reference index).  Manuals
 written in the GNU Texinfo system can also be converted to info files
-suitable for reading online with Emacs or stand-alone GNU Info; use 'make
-info' to create these versions (note that this requires Makeinfo version
+suitable for reading online with Emacs or stand-alone GNU Info; use ‘make
+info’ to create these versions (note that this requires Makeinfo version
 4.5).
 
-   Finally, use 'make check' to find out whether your R system works
+   Finally, use ‘make check’ to find out whether your R system works
 correctly.
 
-   You can also perform a "system-wide" installation using 'make install'.
+   You can also perform a “system-wide” installation using ‘make install’.
 By default, this will install to the following directories:
 
-'${prefix}/bin'
+‘${prefix}/bin’
      the front-end shell script
-'${prefix}/man/man1'
+‘${prefix}/man/man1’
      the man page
-'${prefix}/lib/R'
-     all the rest (libraries, on-line help system, ...).  This is the "R
-     Home Directory" ('R_HOME') of the installed system.
+‘${prefix}/lib/R’
+     all the rest (libraries, on-line help system, ...).  This is the “R
+     Home Directory” (‘R_HOME’) of the installed system.
 
-In the above, 'prefix' is determined during configuration (typically
-'/usr/local') and can be set by running 'configure' with the option
+In the above, ‘prefix’ is determined during configuration (typically
+‘/usr/local’) and can be set by running ‘configure’ with the option
 
      $ ./configure --prefix=/where/you/want/R/to/go
 
 (E.g., the R executable will then be installed into
-'/where/you/want/R/to/go/bin'.)
+‘/where/you/want/R/to/go/bin’.)
 
-   To install info and PDF versions of the manuals, use 'make install-info'
-and 'make install-pdf', respectively.
+   To install info and PDF versions of the manuals, use ‘make install-info’
+and ‘make install-pdf’, respectively.
 
 2.5.2 How can R be installed (Windows)
 --------------------------------------
 
-The 'bin/windows' directory of a CRAN site contains binaries for a base
+The ‘bin/windows’ directory of a CRAN site contains binaries for a base
 distribution and add-on packages from CRAN to run on 64-bit versions of
 Windows 7 and later on x86_64 chips (R 4.1.3 was the last version of R to
 support 32-bit Windows).  The Windows version of R was created by Robert
@@ -357,19 +357,19 @@
    The same directory has links to snapshots of the r-patched and r-devel
 versions of R.
 
-   See the "R for Windows FAQ"
+   See the “R for Windows FAQ”
 (https://CRAN.R-project.org/bin/windows/base/rw-FAQ.html) for more details.
 
 2.5.3 How can R be installed (Mac)
 ----------------------------------
 
-The 'bin/macosx' directory of a CRAN site contains a standard Apple
-installer package to run on macOS 10.13 ('High Sierra') or later, and
-another which runs only on 'Apple Silicon' Macs under macOS 11 ('Big Sur')
+The ‘bin/macosx’ directory of a CRAN site contains a standard Apple
+installer package to run on macOS 10.13 (‘High Sierra’) or later, and
+another which runs only on ‘Apple Silicon’ Macs under macOS 11 (‘Big Sur’)
 or later.  Once downloaded and executed, the installer will install the
 current release of R and R.app, the macOS GUI.  This port of R for macOS is
 maintained by Simon Urbanek <Simon.Urbanek@R-project.org> (and previously by
-Stefano Iacus).  The "R for macOS FAQ"
+Stefano Iacus).  The “R for macOS FAQ”
 (https://CRAN.R-project.org/bin/macosx/RMacOSX-FAQ.html) has more details.
 
    Snapshots of the r-patched and r-devel versions of R are available as
@@ -379,10 +379,10 @@
 =======================================
 
 Binary distributions of R are available on many Unix-like OSes: only some
-can be mentioned here so check your OS's search facilities to see if one is
+can be mentioned here so check your OS’s search facilities to see if one is
 available for yours.
 
-   The 'bin/linux' directory of a CRAN site contains the following packages.
+   The ‘bin/linux’ directory of a CRAN site contains the following packages.
 
                CPU           Versions               Provider
      ----------------------------------------------------------------
@@ -392,27 +392,27 @@
 
    Debian packages, maintained by Dirk Eddelbuettel, have long been part of
 the Debian distribution, and can be accessed through APT, the Debian package
-maintenance tool.  Use e.g. 'apt-get install r-base r-recommended' to
+maintenance tool.  Use e.g. ‘apt-get install r-base r-recommended’ to
 install the R environment and recommended packages.  If you also want to
-build R packages from source, also run 'apt-get install r-base-dev' to
-obtain the additional tools required for this.  So-called "backports" of the
-current R packages for at least the "stable" distribution of Debian are
+build R packages from source, also run ‘apt-get install r-base-dev’ to
+obtain the additional tools required for this.  So-called “backports” of the
+current R packages for at least the “stable” distribution of Debian are
 provided by Johannes Ranke, and available from CRAN.  See
 <https://CRAN.R-project.org/bin/linux/debian/index.html> for details on R
 Debian packages and installing the backports, which should also be suitable
 for other Debian derivatives.  Native backports for Ubuntu are provided by
 Michael Rutter.
 
-   R binaries for Fedora, maintained by Tom "Spot" Callaway, are provided as
-part of the Fedora distribution and can be accessed through 'yum', the RPM
-installer/updater.  Note that the "Software" application (gnome-software),
+   R binaries for Fedora, maintained by Tom “Spot” Callaway, are provided as
+part of the Fedora distribution and can be accessed through ‘yum’, the RPM
+installer/updater.  Note that the “Software” application (gnome-software),
 which is the default GUI for software installation in Fedora 20, cannot be
 used to install R. It is therefore recommended to use the yum command line
-tool.  The Fedora R RPM is a "meta-package" which installs all the user and
-developer components of R (available separately as 'R-core' and 'R-devel'),
-as well as 'R-java', which ensures that R is configured for use with Java.
-The R RPM also installs the standalone R math library ('libRmath' and
-'libRmath-devel'), although this is not necessary to use R. When a new
+tool.  The Fedora R RPM is a “meta-package” which installs all the user and
+developer components of R (available separately as ‘R-core’ and ‘R-devel’),
+as well as ‘R-java’, which ensures that R is configured for use with Java.
+The R RPM also installs the standalone R math library (‘libRmath’ and
+‘libRmath-devel’), although this is not necessary to use R. When a new
 version of R is released, there may be a delay of up to 2 weeks until the
 Fedora RPM becomes publicly available, as it must pass through the Fedora
 review process.  RPMs for a selection of R packages are also provided by
@@ -430,7 +430,7 @@
 ====================================
 
 Online documentation for most of the functions and variables in R exists,
-and can be printed on-screen by typing 'help(NAME)' (or '?NAME') at the R
+and can be printed on-screen by typing ‘help(NAME)’ (or ‘?NAME’) at the R
 prompt, where NAME is the name of the topic help is sought for.  (In the
 case of unary and binary operators and control-flow special forms, the name
 may need to be quoted.)
@@ -442,19 +442,19 @@
 
    The R distribution also comes with the following manuals.
 
-   * "An Introduction to R" ('R-intro') includes information on data types,
+   • “An Introduction to R” (‘R-intro’) includes information on data types,
      programming elements, statistical modeling and graphics.  This document
-     is based on the "Notes on S-PLUS" by Bill Venables and David Smith.
-   * "Writing R Extensions" ('R-exts') currently describes the process of
-     creating R add-on packages, writing R documentation, R's system and
+     is based on the “Notes on S-PLUS” by Bill Venables and David Smith.
+   • “Writing R Extensions” (‘R-exts’) currently describes the process of
+     creating R add-on packages, writing R documentation, R’s system and
      foreign language interfaces, and the R API.
-   * "R Data Import/Export" ('R-data') is a guide to importing and exporting
+   • “R Data Import/Export” (‘R-data’) is a guide to importing and exporting
      data to and from R.
-   * "The R Language Definition" ('R-lang'), a first version of the
-     "Kernighan & Ritchie of R", explains evaluation, parsing, object
+   • “The R Language Definition” (‘R-lang’), a first version of the
+     “Kernighan & Ritchie of R”, explains evaluation, parsing, object
      oriented programming, computing on the language, and so forth.
-   * "R Installation and Administration" ('R-admin').
-   * "R Internals" ('R-ints') is a guide to R's internal structures.  (Added
+   • “R Installation and Administration” (‘R-admin’).
+   • “R Internals” (‘R-ints’) is a guide to R’s internal structures.  (Added
      in R 2.4.0.)
 
    An annotated bibliography (BibTeX format) of R-related publications can
@@ -464,44 +464,44 @@
 
    Books on R by R Core Team members include
 
-     John M. Chambers (2008), "Software for Data Analysis: Programming with
-     R". Springer, New York, ISBN 978-0-387-75935-7,
+     John M. Chambers (2008), “Software for Data Analysis: Programming with
+     R”.  Springer, New York, ISBN 978-0-387-75935-7,
      <https://statweb.stanford.edu/~jmc4/Rbook/>.
 
-     Peter Dalgaard (2008), "Introductory Statistics with R", 2nd edition.
+     Peter Dalgaard (2008), “Introductory Statistics with R”, 2nd edition.
      Springer, ISBN 978-0-387-79053-4,
      <http://publicifsv.sund.ku.dk/~pd/ISwR.html>.
 
-     Robert Gentleman (2008), "R Programming for Bioinformatics".  Chapman &
+     Robert Gentleman (2008), “R Programming for Bioinformatics”.  Chapman &
      Hall/CRC, Boca Raton, FL, ISBN 978-1-420-06367-7,
      <https://master.bioconductor.org/help/publications/books/r-programming-for-bioinformatics/>.
 
-     Stefano M. Iacus (2008), "Simulation and Inference for Stochastic
-     Differential Equations: With R Examples".  Springer, New York, ISBN
+     Stefano M. Iacus (2008), “Simulation and Inference for Stochastic
+     Differential Equations: With R Examples”.  Springer, New York, ISBN
      978-0-387-75838-1.
 
-     Deepayan Sarkar (2007), "Lattice: Multivariate Data Visualization with
-     R". Springer, New York, ISBN 978-0-387-75968-5.
+     Deepayan Sarkar (2007), “Lattice: Multivariate Data Visualization with
+     R”.  Springer, New York, ISBN 978-0-387-75968-5.
 
-     W. John Braun and Duncan J. Murdoch (2007), "A First Course in
-     Statistical Programming with R". Cambridge University Press, Cambridge,
-     ISBN 978-0521872652.
+     W. John Braun and Duncan J. Murdoch (2007), “A First Course in
+     Statistical Programming with R”.  Cambridge University Press,
+     Cambridge, ISBN 978-0521872652.
 
-     P. Murrell (2005), "R Graphics", Chapman & Hall/CRC, ISBN:
+     P. Murrell (2005), “R Graphics”, Chapman & Hall/CRC, ISBN:
      1-584-88486-X,
      <https://www.stat.auckland.ac.nz/~paul/RGraphics/rgraphics.html>.
 
-     William N. Venables and Brian D. Ripley (2002), "Modern Applied
-     Statistics with S" (4th edition).  Springer, ISBN 0-387-95457-0,
+     William N. Venables and Brian D. Ripley (2002), “Modern Applied
+     Statistics with S” (4th edition).  Springer, ISBN 0-387-95457-0,
      <https://www.stats.ox.ac.uk/pub/MASS4/>.
 
-     Jose C. Pinheiro and Douglas M. Bates (2000), "Mixed-Effects Models in
-     S and S-Plus".  Springer, ISBN 0-387-98957-0.
+     Jose C. Pinheiro and Douglas M. Bates (2000), “Mixed-Effects Models in
+     S and S-Plus”.  Springer, ISBN 0-387-98957-0.
 
-   Last, but not least, Ross' and Robert's experience in designing and
-implementing R is described in Ihaka & Gentleman (1996), "R: A Language for
-Data Analysis and Graphics", _Journal of Computational and Graphical
-Statistics_, *5*, 299-314 (doi: 10.1080/10618600.1996.10474713
+   Last, but not least, Ross’ and Robert’s experience in designing and
+implementing R is described in Ihaka & Gentleman (1996), “R: A Language for
+Data Analysis and Graphics”, _Journal of Computational and Graphical
+Statistics_, *5*, 299–314 (doi: 10.1080/10618600.1996.10474713
 (https://doi.org/10.1080/10618600.1996.10474713)).
 
 2.8 Citing R
@@ -519,10 +519,10 @@
        url          = {https://www.R-project.org}
      }
 where YEAR is the release year of the version of R used and can determined
-as 'R.version$year'.
+as ‘R.version$year’.
 
    Citation strings (or BibTeX entries) for R and R packages can also be
-obtained by 'citation()'.
+obtained by ‘citation()’.
 
 2.9 What mailing lists exist for R?
 ===================================
@@ -530,21 +530,21 @@
 Thanks to Martin Maechler <Martin.Maechler@R-project.org>, there are several
 mailing lists devoted to R, including the following:
 
-'R-announce'
+‘R-announce’
      A moderated list for major announcements about the development of R and
      the availability of new code.
-'R-packages'
+‘R-packages’
      A moderated list for announcements on the availability of new or
      enhanced contributed packages.
-'R-help'
-     The 'main' R mailing list, for discussion about problems and solutions
+‘R-help’
+     The ‘main’ R mailing list, for discussion about problems and solutions
      encountered using R, including using R packages in the standard R
-     distribution and on CRAN; announcements (not covered by 'R-announce' or
-     'R-packages'); the availability of new functionality for R and
+     distribution and on CRAN; announcements (not covered by ‘R-announce’ or
+     ‘R-packages’); the availability of new functionality for R and
      documentation of R; and for posting nice examples and benchmarks.
-'R-devel'
+‘R-devel’
      This list is for questions and discussion about code development in R.
-'R-package-devel'
+‘R-package-devel’
      A list which provides a forum for those developing R packages.
 
 Please read the posting guide (https://www.R-project.org/posting-guide.html)
@@ -559,14 +559,14 @@
    Convenient access to information on these lists, subscription, and
 archives is provided by the web interface at
 <https://stat.ethz.ch/mailman/listinfo/>.  One can also subscribe (or
-unsubscribe) via email, e.g. to R-help by sending 'subscribe' (or
-'unsubscribe') in the _body_ of the message (not in the subject!)  to
+unsubscribe) via email, e.g. to R-help by sending ‘subscribe’ (or
+‘unsubscribe’) in the _body_ of the message (not in the subject!)  to
 <R-help-request@lists.R-project.org>.
 
    Send email to <R-help@lists.R-project.org> to send a message to everyone
 on the R-help mailing list.  Subscription and posting to the other lists is
-done analogously, with 'R-help' replaced by 'R-announce', 'R-packages', and
-'R-devel', respectively.  Note that the R-announce and R-packages lists are
+done analogously, with ‘R-help’ replaced by ‘R-announce’, ‘R-packages’, and
+‘R-devel’, respectively.  Note that the R-announce and R-packages lists are
 gatewayed into R-help.  Hence, you should subscribe to either of them only
 in case you are not subscribed to R-help.
 
@@ -586,7 +586,7 @@
 2.10 What is CRAN?
 ==================
 
-The "Comprehensive R Archive Network" (CRAN) is a collection of sites which
+The “Comprehensive R Archive Network” (CRAN) is a collection of sites which
 carry identical material, consisting of the R distribution(s), the
 contributed extensions, documentation for R, and binaries.
 
@@ -606,7 +606,7 @@
 Windows).  CRAN also provides access to documentation on R, existing mailing
 lists and the R Bug Tracking system.
 
-   Since March 2016, "old" material is made available from a central CRAN
+   Since March 2016, “old” material is made available from a central CRAN
 archive server (<https://CRAN-archive.R-project.org/>).
 
    Please always use the URL of the master site when referring to CRAN.
@@ -623,7 +623,7 @@
 purposes (e.g., in business or in consulting).  The GPL, like all Open
 Source licenses, permits all and any use of the package.  It only restricts
 distribution of R or of other programs containing code from R. This is made
-clear in clause 6 ("No Discrimination Against Fields of Endeavor") of the
+clear in clause 6 (“No Discrimination Against Fields of Endeavor”) of the
 Open Source Definition (https://opensource.org/osd/):
 
      The license must not restrict anyone from making use of the program in
@@ -640,7 +640,7 @@
 
    Most add-on packages, including all recommended ones, also explicitly
 allow commercial use in this way.  A few packages are restricted to
-"non-commercial use"; you should contact the author to clarify whether these
+“non-commercial use”; you should contact the author to clarify whether these
 may be used or seek the advice of your legal counsel.
 
    None of the discussion in this section constitutes legal advice.  The R
@@ -651,7 +651,7 @@
 
 The name is partly based on the (first) names of the first two R authors
 (Robert Gentleman and Ross Ihaka), and partly a play on the name of the Bell
-Labs language 'S' (*note What is S?::).
+Labs language ‘S’ (*note What is S?::).
 
 2.13 What is the R Foundation?
 ==============================
@@ -674,8 +674,8 @@
 to the best in SVN, daily built and checked packages, mailing lists, bug
 tracking, message boards/forums, site hosting, permanent file archival, full
 backups, and total web-based administration.  For more information, see the
-R-Forge web page and Stefan Theußl and Achim Zeileis (2009), "Collaborative
-software development using R-Forge", _The R Journal_, *1*(1):9-14.
+R-Forge web page and Stefan Theußl and Achim Zeileis (2009), “Collaborative
+software development using R-Forge”, _The R Journal_, *1*(1):9–14.
 
 3 R and S
 *********
@@ -698,53 +698,53 @@
    The evolution of the S language is characterized by four books by John
 Chambers and coauthors, which are also the primary references for S.
 
-   * Richard A. Becker and John M. Chambers (1984), "S. An Interactive
-     Environment for Data Analysis and Graphics," Monterey: Wadsworth and
+   • Richard A. Becker and John M. Chambers (1984), “S. An Interactive
+     Environment for Data Analysis and Graphics,” Monterey: Wadsworth and
      Brooks/Cole.
 
-     This is also referred to as the "_Brown Book_", and of historical
+     This is also referred to as the “_Brown Book_”, and of historical
      interest only.
 
-   * Richard A. Becker, John M. Chambers and Allan R. Wilks (1988), "The New
-     S Language," London: Chapman & Hall.
+   • Richard A. Becker, John M. Chambers and Allan R. Wilks (1988), “The New
+     S Language,” London: Chapman & Hall.
 
-     This book is often called the "_Blue Book_", and introduced what is now
+     This book is often called the “_Blue Book_”, and introduced what is now
      known as S version 2.
 
-   * John M. Chambers and Trevor J. Hastie (1992), "Statistical Models in
-     S," London: Chapman & Hall.
+   • John M. Chambers and Trevor J. Hastie (1992), “Statistical Models in
+     S,” London: Chapman & Hall.
 
-     This is also called the "_White Book_", and introduced S version 3,
+     This is also called the “_White Book_”, and introduced S version 3,
      which added structures to facilitate statistical modeling in S.
 
-   * John M. Chambers (1998), "Programming with Data," New York: Springer,
+   • John M. Chambers (1998), “Programming with Data,” New York: Springer,
      ISBN 0-387-98503-4 (<https://statweb.stanford.edu/~jmc4/Sbook/>).
 
-     This "_Green Book_" describes version 4 of S, a major revision of S
+     This “_Green Book_” describes version 4 of S, a major revision of S
      designed by John Chambers to improve its usefulness at every stage of
      the programming process.
 
    See <https://statweb.stanford.edu/~jmc4/papers/96.7.ps> for further
-information on the "Evolution of the S Language".
+information on the “Evolution of the S Language”.
 
 3.2 What is S-PLUS?
 ===================
 
 S-PLUS is a value-added version of S sold by TIBCO Software Inc
-(https://www.tibco.com/) as 'TIBCO Spotfire S+'.  See
+(https://www.tibco.com/) as ‘TIBCO Spotfire S+’.  See
 <https://en.wikipedia.org/wiki/S-PLUS> for more information.
 
 3.3 What are the differences between R and S?
 =============================================
 
 We can regard S as a language with three current implementations or
-"engines", the "old S engine" (S version 3; S-PLUS 3.x and 4.x), the "new S
-engine" (S version 4; S-PLUS 5.x and above), and R. Given this
-understanding, asking for "the differences between R and S" really amounts
+“engines”, the “old S engine” (S version 3; S-PLUS 3.x and 4.x), the “new S
+engine” (S version 4; S-PLUS 5.x and above), and R. Given this
+understanding, asking for “the differences between R and S” really amounts
 to asking for the specifics of the R implementation of the S language, i.e.,
 the difference between the R and S _engines_.
 
-   For the remainder of this section, "S" refers to the S engines and not
+   For the remainder of this section, “S” refers to the S engines and not
 the S language.
 
 3.3.1 Lexical scoping
@@ -769,7 +769,7 @@
        n * sq()
      }
 
-   Under S, 'sq()' does not "know" about the variable 'n' unless it is
+   Under S, ‘sq()’ does not “know” about the variable ‘n’ unless it is
 defined globally:
 
      S> cube(2)
@@ -779,19 +779,19 @@
      S> cube(2)
      [1] 18
 
-   In R, the "environment" created when 'cube()' was invoked is also looked
+   In R, the “environment” created when ‘cube()’ was invoked is also looked
 in:
 
      R> cube(2)
      [1] 8
 
-   As a more "interesting" real-world problem, suppose you want to write a
+   As a more “interesting” real-world problem, suppose you want to write a
 function which returns the density function of the r-th order statistic from
 a sample of size n from a (continuous) distribution.  For simplicity, we
 shall use both the cdf and pdf of the distribution as explicit arguments.
 (Example compiled from various postings by Luke Tierney.)
 
-   The S-PLUS documentation for 'call()' basically suggests the following:
+   The S-PLUS documentation for ‘call()’ basically suggests the following:
 
      dorder <- function(n, r, pfun, dfun) {
        f <- function(x) NULL
@@ -806,11 +806,11 @@
        f
      }
 
-Rather tricky, isn't it?  The code uses the fact that in S, functions are
+Rather tricky, isn’t it?  The code uses the fact that in S, functions are
 just lists of special mode with the function body as the last argument, and
 hence does not work in R (one could make the idea work, though).
 
-   A version which makes heavy use of 'substitute()' and seems to work under
+   A version which makes heavy use of ‘substitute()’ and seems to work under
 both S and R is
 
      dorder <- function(n, r, pfun, dfun) {
@@ -820,7 +820,7 @@
                             a = r - 1, b = n - r, K = con)))
      }
 
-(the 'eval()' is not needed in S).
+(the ‘eval()’ is not needed in S).
 
    However, in R there is a much easier solution:
 
@@ -831,7 +831,7 @@
        }
      }
 
-This seems to be the "natural" implementation, and it works because the free
+This seems to be the “natural” implementation, and it works because the free
 variables in the returned function can be looked up in the defining
 environment (this is lexical scope).
 
@@ -839,7 +839,7 @@
 along with all variable bindings needed for evaluating it.  Since in the
 above version, the free variables in the value function are not modified,
 you can actually use it in S as well if you abstract out the closure
-operation into a function 'MC()' (for "make closure"):
+operation into a function ‘MC()’ (for “make closure”):
 
      dorder <- function(n, r, pfun, dfun) {
        con <- round(exp(lgamma(n + 1) - lgamma(r) - lgamma(n - r + 1)))
@@ -850,11 +850,11 @@
      }
 
    Given the appropriate definitions of the closure operator, this works in
-both R and S, and is much "cleaner" than a substitute/eval solution (or one
+both R and S, and is much “cleaner” than a substitute/eval solution (or one
 which overrules the default scoping rules by using explicit access to
 evaluation frames, as is of course possible in both R and S).
 
-   For R, 'MC()' simply is
+   For R, ‘MC()’ simply is
 
      MC <- function(f, env) f
 
@@ -888,27 +888,27 @@
 
    Nested lexically scoped functions allow using function closures and
 maintaining local state.  A simple example (taken from Abelson and Sussman)
-is obtained by typing 'demo("scoping")' at the R prompt.  Further
-information is provided in the standard R reference "R: A Language for Data
-Analysis and Graphics" (*note What documentation exists for R?::) and in
-Robert Gentleman and Ross Ihaka (2000), "Lexical Scope and Statistical
-Computing", _Journal of Computational and Graphical Statistics_, *9*,
-491-508 (doi: 10.1080/10618600.2000.10474895
+is obtained by typing ‘demo("scoping")’ at the R prompt.  Further
+information is provided in the standard R reference “R: A Language for Data
+Analysis and Graphics” (*note What documentation exists for R?::) and in
+Robert Gentleman and Ross Ihaka (2000), “Lexical Scope and Statistical
+Computing”, _Journal of Computational and Graphical Statistics_, *9*,
+491–508 (doi: 10.1080/10618600.2000.10474895
 (https://doi.org/10.1080/10618600.2000.10474895)).
 
    Nested lexically scoped functions also imply a further major difference.
 Whereas S stores all objects as separate files in a directory somewhere
-(usually '.Data' under the current directory), R does not.  All objects in R
+(usually ‘.Data’ under the current directory), R does not.  All objects in R
 are stored internally.  When R is started up it grabs a piece of memory and
 uses it to store the objects.  R performs its own memory management of this
 piece of memory, growing and shrinking its size as needed.  Having
 everything in memory is necessary because it is not really possible to
-externally maintain all relevant "environments" of symbol/value pairs.  This
+externally maintain all relevant “environments” of symbol/value pairs.  This
 difference also seems to make R _faster_ than S.
 
    The down side is that if R crashes you will lose all the work for the
-current session.  Saving and restoring the memory "images" (the functions
-and data stored in R's internal memory at any time) can be a bit slow,
+current session.  Saving and restoring the memory “images” (the functions
+and data stored in R’s internal memory at any time) can be a bit slow,
 especially if they are big.  In S this does not happen, because everything
 is saved in disk files and if you crash nothing is likely to happen to them.
 (In fact, one might conjecture that the S developers felt that the price of
@@ -917,11 +917,11 @@
 consider saving often (see *note How can I save my workspace?::) to
 safeguard against possible crashes.  Other possibilities are logging your
 sessions, or have your R commands stored in text files which can be read in
-using 'source()'.
+using ‘source()’.
 
      Note: If you run R from within Emacs (see *note R and Emacs::), you can
      save the contents of the interaction buffer to a file and conveniently
-     manipulate it using 'ess-transcript-mode', as well as save source
+     manipulate it using ‘ess-transcript-mode’, as well as save source
      copies of all functions and data used.
 
 3.3.2 Models
@@ -929,175 +929,175 @@
 
 There are some differences in the modeling code, such as
 
-   * Whereas in S, you would use 'lm(y ~ x^3)' to regress 'y' on 'x^3', in
-     R, you have to insulate powers of numeric vectors (using 'I()'), i.e.,
-     you have to use 'lm(y ~ I(x^3))'.
-   * The glm family objects are implemented differently in R and S. The same
+   • Whereas in S, you would use ‘lm(y ~ x^3)’ to regress ‘y’ on ‘x^3’, in
+     R, you have to insulate powers of numeric vectors (using ‘I()’), i.e.,
+     you have to use ‘lm(y ~ I(x^3))’.
+   • The glm family objects are implemented differently in R and S. The same
      functionality is available but the components have different names.
-   * Option 'na.action' is set to '"na.omit"' by default in R, but not set
+   • Option ‘na.action’ is set to ‘"na.omit"’ by default in R, but not set
      in S.
-   * Terms objects are stored differently.  In S a terms object is an
+   • Terms objects are stored differently.  In S a terms object is an
      expression with attributes, in R it is a formula with attributes.  The
      attributes have the same names but are mostly stored differently.
-   * Finally, in R 'y ~ x + 0' is an alternative to 'y ~ x - 1' for
+   • Finally, in R ‘y ~ x + 0’ is an alternative to ‘y ~ x - 1’ for
      specifying a model with no intercept.  Models with no parameters at all
-     can be specified by 'y ~ 0'.
+     can be specified by ‘y ~ 0’.
 
 3.3.3 Others
 ------------
 
 Apart from lexical scoping and its implications, R follows the S language
 definition in the Blue and White Books as much as possible, and hence really
-is an "implementation" of S. There are some intentional differences where
-the behavior of S is considered "not clean".  In general, the rationale is
+is an “implementation” of S. There are some intentional differences where
+the behavior of S is considered “not clean”.  In general, the rationale is
 that R should help you detect programming errors, while at the same time
 being as compatible as possible with S.
 
    Some known differences are the following.
 
-   * In R, if 'x' is a list, then 'x[i] <- NULL' and 'x[[i]] <- NULL' remove
-     the specified elements from 'x'.  The first of these is incompatible
-     with S, where it is a no-op.  (Note that you can set elements to 'NULL'
-     using 'x[i] <- list(NULL)'.)
+   • In R, if ‘x’ is a list, then ‘x[i] <- NULL’ and ‘x[[i]] <- NULL’ remove
+     the specified elements from ‘x’.  The first of these is incompatible
+     with S, where it is a no-op.  (Note that you can set elements to ‘NULL’
+     using ‘x[i] <- list(NULL)’.)
 
-   * In S, the functions named '.First' and '.Last' in the '.Data' directory
+   • In S, the functions named ‘.First’ and ‘.Last’ in the ‘.Data’ directory
      can be used for customizing, as they are executed at the very beginning
      and end of a session, respectively.
 
-     In R, the startup mechanism is as follows.  Unless '--no-environ' was
+     In R, the startup mechanism is as follows.  Unless ‘--no-environ’ was
      given on the command line, R searches for site and user files to
      process for setting environment variables.  Then, R searches for a
      site-wide startup profile unless the command line option
-     '--no-site-file' was given.  This code is loaded in package *base*.
-     Then, unless '--no-init-file' was given, R searches for a user profile
+     ‘--no-site-file’ was given.  This code is loaded in package *base*.
+     Then, unless ‘--no-init-file’ was given, R searches for a user profile
      file, and sources it into the user workspace.  It then loads a saved
-     image of the user workspace from '.RData' in case there is one (unless
-     '--no-restore-data' or '--no-restore' were specified).  Next, a
-     function '.First()' is run if found on the search path.  Finally,
-     function '.First.sys' in the *base* package is run.  When terminating
-     an R session, by default a function '.Last' is run if found on the
-     search path, followed by '.Last.sys'.  If needed, the functions
-     '.First()' and '.Last()' should be defined in the appropriate startup
-     profiles.  See the help pages for '.First' and '.Last' for more
+     image of the user workspace from ‘.RData’ in case there is one (unless
+     ‘--no-restore-data’ or ‘--no-restore’ were specified).  Next, a
+     function ‘.First()’ is run if found on the search path.  Finally,
+     function ‘.First.sys’ in the *base* package is run.  When terminating
+     an R session, by default a function ‘.Last’ is run if found on the
+     search path, followed by ‘.Last.sys’.  If needed, the functions
+     ‘.First()’ and ‘.Last()’ should be defined in the appropriate startup
+     profiles.  See the help pages for ‘.First’ and ‘.Last’ for more
      details.
 
-   * In R, 'T' and 'F' are just variables being set to 'TRUE' and 'FALSE',
+   • In R, ‘T’ and ‘F’ are just variables being set to ‘TRUE’ and ‘FALSE’,
      respectively, but are not reserved words as in S and hence can be
      overwritten by the user.  (This helps e.g. when you have factors with
-     levels '"T"' or '"F"'.)  Hence, when writing code you should always use
-     'TRUE' and 'FALSE'.
+     levels ‘"T"’ or ‘"F"’.)  Hence, when writing code you should always use
+     ‘TRUE’ and ‘FALSE’.
 
-   * In R, 'dyn.load()' can only load _shared objects_, as created for
-     example by 'R CMD SHLIB'.
+   • In R, ‘dyn.load()’ can only load _shared objects_, as created for
+     example by ‘R CMD SHLIB’.
 
-   * In R, 'attach()' currently only works for lists and data frames, but
-     not for directories.  (In fact, 'attach()' also works for R data files
-     created with 'save()', which is analogous to attaching directories in
+   • In R, ‘attach()’ currently only works for lists and data frames, but
+     not for directories.  (In fact, ‘attach()’ also works for R data files
+     created with ‘save()’, which is analogous to attaching directories in
      S.) Also, you cannot attach at position 1.
 
-   * Categories do not exist in R, and never will as they are deprecated now
+   • Categories do not exist in R, and never will as they are deprecated now
      in S. Use factors instead.
 
-   * In R, 'For()' loops are not necessary and hence not supported.
+   • In R, ‘For()’ loops are not necessary and hence not supported.
 
-   * In R, 'assign()' uses the argument 'envir=' rather than 'where=' as in
+   • In R, ‘assign()’ uses the argument ‘envir=’ rather than ‘where=’ as in
      S.
 
-   * The random number generators are different, and the seeds have
+   • The random number generators are different, and the seeds have
      different length.
 
-   * R passes integer objects to C as 'int *' rather than 'long *' as in S.
+   • R passes integer objects to C as ‘int *’ rather than ‘long *’ as in S.
 
-   * R has no single precision storage mode.  However, as of version 0.65.1,
+   • R has no single precision storage mode.  However, as of version 0.65.1,
      there is a single precision interface to C/FORTRAN subroutines.
 
-   * By default, 'ls()' returns the names of the objects in the current
+   • By default, ‘ls()’ returns the names of the objects in the current
      (under R) and global (under S) environment, respectively.  For example,
      given
 
           x <- 1; fun <- function() {y <- 1; ls()}
 
-     then 'fun()' returns '"y"' in R and '"x"' (together with the rest of
+     then ‘fun()’ returns ‘"y"’ in R and ‘"x"’ (together with the rest of
      the global environment) in S.
 
-   * R allows for zero-extent matrices (and arrays, i.e., some elements of
-     the 'dim' attribute vector can be 0).  This has been determined a
+   • R allows for zero-extent matrices (and arrays, i.e., some elements of
+     the ‘dim’ attribute vector can be 0).  This has been determined a
      useful feature as it helps reducing the need for special-case tests for
-     empty subsets.  For example, if 'x' is a matrix, 'x[, FALSE]' is not
-     'NULL' but a "matrix" with 0 columns.  Hence, such objects need to be
-     tested for by checking whether their 'length()' is zero (which works in
-     both R and S), and not using 'is.null()'.
+     empty subsets.  For example, if ‘x’ is a matrix, ‘x[, FALSE]’ is not
+     ‘NULL’ but a “matrix” with 0 columns.  Hence, such objects need to be
+     tested for by checking whether their ‘length()’ is zero (which works in
+     both R and S), and not using ‘is.null()’.
 
-   * Named vectors are considered vectors in R but not in S (e.g.,
-     'is.vector(c(a = 1:3))' returns 'FALSE' in S and 'TRUE' in R).
+   • Named vectors are considered vectors in R but not in S (e.g.,
+     ‘is.vector(c(a = 1:3))’ returns ‘FALSE’ in S and ‘TRUE’ in R).
 
-   * Data frames are not considered as matrices in R (i.e., if 'DF' is a
-     data frame, then 'is.matrix(DF)' returns 'FALSE' in R and 'TRUE' in S).
+   • Data frames are not considered as matrices in R (i.e., if ‘DF’ is a
+     data frame, then ‘is.matrix(DF)’ returns ‘FALSE’ in R and ‘TRUE’ in S).
 
-   * R by default uses treatment contrasts in the unordered case, whereas S
+   • R by default uses treatment contrasts in the unordered case, whereas S
      uses the Helmert ones.  This is a deliberate difference reflecting the
      opinion that treatment contrasts are more natural.
 
-   * In R, the argument of a replacement function which corresponds to the
-     right hand side must be named 'value'.  E.g., 'f(a) <- b' is evaluated
-     as 'a <- "f<-"(a, value = b)'.  S always takes the last argument,
+   • In R, the argument of a replacement function which corresponds to the
+     right hand side must be named ‘value’.  E.g., ‘f(a) <- b’ is evaluated
+     as ‘a <- "f<-"(a, value = b)’.  S always takes the last argument,
      irrespective of its name.
 
-   * In S, 'substitute()' searches for names for substitution in the given
+   • In S, ‘substitute()’ searches for names for substitution in the given
      expression in three places: the actual and the default arguments of the
      matching call, and the local frame (in that order).  R looks in the
-     local frame only, with the special rule to use a "promise" if a
+     local frame only, with the special rule to use a “promise” if a
      variable is not evaluated.  Since the local frame is initialized with
      the actual arguments or the default expressions, this is usually
      equivalent to S, until assignment takes place.
 
-   * In S, the index variable in a 'for()' loop is local to the inside of
-     the loop.  In R it is local to the environment where the 'for()'
+   • In S, the index variable in a ‘for()’ loop is local to the inside of
+     the loop.  In R it is local to the environment where the ‘for()’
      statement is executed.
 
-   * In S, 'tapply(simplify=TRUE)' returns a vector where R returns a
+   • In S, ‘tapply(simplify=TRUE)’ returns a vector where R returns a
      one-dimensional array (which can have named dimnames).
 
-   * In S(-PLUS) the C locale is used, whereas in R the current operating
+   • In S(-PLUS) the C locale is used, whereas in R the current operating
      system locale is used for determining which characters are alphanumeric
      and how they are sorted.  This affects the set of valid names for R
      objects (for example accented chars may be allowed in R) and ordering
-     in sorts and comparisons (such as whether '"aA" < "Bb"' is true or
+     in sorts and comparisons (such as whether ‘"aA" < "Bb"’ is true or
      false).  From version 1.2.0 the locale can be (re-)set in R by the
-     'Sys.setlocale()' function.
+     ‘Sys.setlocale()’ function.
 
-   * In S, 'missing(ARG)' remains 'TRUE' if ARG is subsequently modified; in
-     R it doesn't.
+   • In S, ‘missing(ARG)’ remains ‘TRUE’ if ARG is subsequently modified; in
+     R it doesn’t.
 
-   * From R version 1.3.0, 'data.frame' strips 'I()' when creating (column)
+   • From R version 1.3.0, ‘data.frame’ strips ‘I()’ when creating (column)
      names.
 
-   * In R, the string '"NA"' is not treated as a missing value in a
-     character variable.  Use 'as.character(NA)' to create a missing
+   • In R, the string ‘"NA"’ is not treated as a missing value in a
+     character variable.  Use ‘as.character(NA)’ to create a missing
      character value.
 
-   * R disallows repeated formal arguments in function calls.
+   • R disallows repeated formal arguments in function calls.
 
-   * In S, 'dump()', 'dput()' and 'deparse()' are essentially different
+   • In S, ‘dump()’, ‘dput()’ and ‘deparse()’ are essentially different
      interfaces to the same code.  In R from version 2.0.0, this is only
-     true if the same 'control' argument is used, but by default it is not.
-     By default 'dump()' tries to write code that will evaluate to reproduce
-     the object, whereas 'dput()' and 'deparse()' default to options for
+     true if the same ‘control’ argument is used, but by default it is not.
+     By default ‘dump()’ tries to write code that will evaluate to reproduce
+     the object, whereas ‘dput()’ and ‘deparse()’ default to options for
      producing deparsed code that is readable.
 
-   * In R, indexing a vector, matrix, array or data frame with '[' using a
-     character vector index looks only for exact matches (whereas '[[' and
-     '$' allow partial matches).  In S, '[' allows partial matches.
-
-   * S has a two-argument version of 'atan' and no 'atan2'.  A call in S
-     such as 'atan(x1, x2)' is equivalent to R's 'atan2(x1, x2)'.  However,
-     beware of named arguments since S's 'atan(x = a, y = b)' is equivalent
-     to R's 'atan2(y = a, x = b)' with the meanings of 'x' and 'y'
+   • In R, indexing a vector, matrix, array or data frame with ‘[’ using a
+     character vector index looks only for exact matches (whereas ‘[[’ and
+     ‘$’ allow partial matches).  In S, ‘[’ allows partial matches.
+
+   • S has a two-argument version of ‘atan’ and no ‘atan2’.  A call in S
+     such as ‘atan(x1, x2)’ is equivalent to R’s ‘atan2(x1, x2)’.  However,
+     beware of named arguments since S’s ‘atan(x = a, y = b)’ is equivalent
+     to R’s ‘atan2(y = a, x = b)’ with the meanings of ‘x’ and ‘y’
      interchanged.  (R used to have undocumented support for a two-argument
-     'atan' with positional arguments, but this has been withdrawn to avoid
+     ‘atan’ with positional arguments, but this has been withdrawn to avoid
      further confusion.)
 
-   * Numeric constants with no fractional and exponent (i.e., only integer)
+   • Numeric constants with no fractional and exponent (i.e., only integer)
      part are taken as integer in S-PLUS 6.x or later, but as double in R.
 
    There are also differences which are not intentional, and result from
@@ -1111,17 +1111,17 @@
 
 Since almost anything you can do in R has source code that you could port to
 S-PLUS with little effort there will never be much you can do in R that you
-couldn't do in S-PLUS if you wanted to.  (Note that using lexical scoping
+couldn’t do in S-PLUS if you wanted to.  (Note that using lexical scoping
 may simplify matters considerably, though.)
 
    R offers several graphics features that S-PLUS does not, such as finer
 handling of line types, more convenient color handling (via palettes), gamma
 correction for color, and, most importantly, mathematical annotation in plot
 texts, via input expressions reminiscent of TeX constructs.  See the help
-page for 'plotmath', which features an impressive on-line example.  More
-details can be found in Paul Murrell and Ross Ihaka (2000), "An Approach to
-Providing Mathematical Annotation in Plots", _Journal of Computational and
-Graphical Statistics_, *9*, 582-599 (doi: 10.1080/10618600.2000.10474900
+page for ‘plotmath’, which features an impressive on-line example.  More
+details can be found in Paul Murrell and Ross Ihaka (2000), “An Approach to
+Providing Mathematical Annotation in Plots”, _Journal of Computational and
+Graphical Statistics_, *9*, 582–599 (doi: 10.1080/10618600.2000.10474900
 (https://doi.org/10.1080/10618600.2000.10474900)).
 
 3.5 What is R-plus?
@@ -1141,17 +1141,17 @@
 4 R Web Interfaces
 ******************
 
-Please refer to the CRAN task view on "Web Technologies and Services"
+Please refer to the CRAN task view on “Web Technologies and Services”
 (<https://CRAN.R-project.org/view=WebTechnologies>), specifically section
-"Web and Server Frameworks", for up-to-date information on R web interface
+“Web and Server Frameworks”, for up-to-date information on R web interface
 packages.
 
-   Early references on R web interfaces include Jeff Banfield (1999), "Rweb:
-Web-based Statistical Analysis" (doi: 10.18637/jss.v004.i01
-(https://doi.org/10.18637/jss.v004.i01)), David Firth (2003), "CGIwithR:
-Facilities for processing web forms using R" (doi: 10.18637/jss.v008.i10
+   Early references on R web interfaces include Jeff Banfield (1999), “Rweb:
+Web-based Statistical Analysis” (doi: 10.18637/jss.v004.i01
+(https://doi.org/10.18637/jss.v004.i01)), David Firth (2003), “CGIwithR:
+Facilities for processing web forms using R” (doi: 10.18637/jss.v008.i10
 (https://doi.org/10.18637/jss.v008.i10)), and Angelo Mineo and Alfredo
-Pontillo (2006), "Using R via PHP for Teaching Purposes: R-php"
+Pontillo (2006), “Using R via PHP for Teaching Purposes: R-php”
 (doi: 10.18637/jss.v017.i04 (https://doi.org/10.18637/jss.v017.i04)).
 
 5 R Add-On Packages
@@ -1200,21 +1200,21 @@
 5.1.2 Add-on packages from CRAN
 -------------------------------
 
-The CRAN 'src/contrib' area contains a wealth of add-on packages, including
+The CRAN ‘src/contrib’ area contains a wealth of add-on packages, including
 the following _recommended_ packages which are to be included in all binary
 distributions of R.
 
 *KernSmooth*
      Functions for kernel smoothing (and density estimation) corresponding
-     to the book "Kernel Smoothing" by M. P. Wand and M. C. Jones, 1995.
+     to the book “Kernel Smoothing” by M. P. Wand and M. C. Jones, 1995.
 *MASS*
      Functions and datasets from the main package of Venables and Ripley,
-     "Modern Applied Statistics with S".
+     “Modern Applied Statistics with S”.
 *Matrix*
      Support for spares and dense matrices
 *boot*
-     Functions and datasets for bootstrapping from the book "Bootstrap
-     Methods and Their Applications" by A. C. Davison and D. V. Hinkley,
+     Functions and datasets for bootstrapping from the book “Bootstrap
+     Methods and Their Applications” by A. C. Davison and D. V. Hinkley,
      1997, Cambridge University Press.
 *class*
      Functions for classification (k-nearest neighbor and LVQ).
@@ -1233,13 +1233,13 @@
 *nlme*
      Fit and compare Gaussian linear and nonlinear mixed-effects models.
 *nnet*
-     Software for single hidden layer perceptrons ("feed-forward neural
-     networks"), and for multinomial log-linear models.
+     Software for single hidden layer perceptrons (“feed-forward neural
+     networks”), and for multinomial log-linear models.
 *rpart*
      Recursive PARTitioning and regression trees.
 *spatial*
-     Functions for kriging and point pattern analysis from "Modern Applied
-     Statistics with S" by W. Venables and B. Ripley.
+     Functions for kriging and point pattern analysis from “Modern Applied
+     Statistics with S” by W. Venables and B. Ripley.
 *survival*
      Functions for survival analysis, including penalized likelihood.
    See the CRAN contributed packages page for more information.
@@ -1279,13 +1279,13 @@
 =========================================
 
 (Unix-like only.)  The add-on packages on CRAN come as gzipped tar files
-named 'PKG_VERSION.tar.gz'.  Let PATH be the path to such a package file.
-Provided that 'tar' and 'gzip' are available on your system, type
+named ‘PKG_VERSION.tar.gz’.  Let PATH be the path to such a package file.
+Provided that ‘tar’ and ‘gzip’ are available on your system, type
 
      $ R CMD INSTALL PATH/PKG_VERSION.tar.gz
 
 at the shell prompt to install to the library tree rooted at the first
-directory in your library search path (see the help page for '.libPaths()'
+directory in your library search path (see the help page for ‘.libPaths()’
 for details on how the search path is determined).
 
    To install to another tree (e.g., your private one), use
@@ -1296,7 +1296,7 @@
 
    Even more conveniently, you can install and automatically update packages
 from within R if you have access to repositories such as CRAN.  See the help
-page for 'available.packages()' for more information.
+page for ‘available.packages()’ for more information.
 
 5.3 How can add-on packages be used?
 ====================================
@@ -1348,7 +1348,7 @@
           tools         Tools for Package Development
           utils         The R Utils Package
 
-   You can "load" the installed package PKG by
+   You can “load” the installed package PKG by
 
      library(PKG)
 
@@ -1361,8 +1361,8 @@
 
      detach("package:PKG", unload = TRUE)
 
-(where 'unload = TRUE' is needed only for packages with a namespace, see
-'?unload').
+(where ‘unload = TRUE’ is needed only for packages with a namespace, see
+‘?unload’).
 
 5.4 How can add-on packages be removed?
 =======================================
@@ -1372,7 +1372,7 @@
      $ R CMD REMOVE PKG_1 ... PKG_N
 
 to remove the packages PKG_1, ..., PKG_N from the library tree rooted at the
-first directory given in 'R_LIBS' if this is set and non-null, and from the
+first directory given in ‘R_LIBS’ if this is set and non-null, and from the
 default library otherwise.
 
    To remove from library LIB, do
@@ -1382,18 +1382,18 @@
 5.5 How can I create an R package?
 ==================================
 
-A package consists of a subdirectory containing a file 'DESCRIPTION' and the
-subdirectories 'R', 'data', 'demo', 'exec', 'inst', 'man', 'po', 'src', and
-'tests' (some of which can be missing).  The package subdirectory may also
-contain files 'INDEX', 'NAMESPACE', 'configure', 'cleanup', 'LICENSE',
-'LICENCE', 'COPYING' and 'NEWS'.
+A package consists of a subdirectory containing a file ‘DESCRIPTION’ and the
+subdirectories ‘R’, ‘data’, ‘demo’, ‘exec’, ‘inst’, ‘man’, ‘po’, ‘src’, and
+‘tests’ (some of which can be missing).  The package subdirectory may also
+contain files ‘INDEX’, ‘NAMESPACE’, ‘configure’, ‘cleanup’, ‘LICENSE’,
+‘LICENCE’, ‘COPYING’ and ‘NEWS’.
 
-   See section "Creating R packages" in 'Writing R Extensions', for details.
+   See section “Creating R packages” in ‘Writing R Extensions’, for details.
 This manual is included in the R distribution, *note What documentation
 exists for R?::, and gives information on package structure, the configure
 and cleanup mechanisms, and on automated package checking and building.
 
-   R version 1.3.0 has added the function 'package.skeleton()' which will
+   R version 1.3.0 has added the function ‘package.skeleton()’ which will
 set up directories, save data and code, and create skeleton help files for a
 set of R functions and datasets.
 
@@ -1418,7 +1418,7 @@
 6.1 Is there Emacs support for R?
 =================================
 
-There is an Emacs package called ESS ("Emacs Speaks Statistics") which
+There is an Emacs package called ESS (“Emacs Speaks Statistics”) which
 provides a standard interface between statistical programs and statistical
 processes.  It is intended to provide assistance for interactive statistical
 programming and data analysis.  Languages supported include: S dialects (R,
@@ -1455,15 +1455,15 @@
 
    Please send bug reports and suggestions on ESS to
 <ESS-bugs@r-project.org>.  The easiest way to do this from is within Emacs
-by typing 'M-x ess-submit-bug-report' or using the [ESS] or [iESS] pulldown
+by typing ‘M-x ess-submit-bug-report’ or using the [ESS] or [iESS] pulldown
 menus.
 
 6.2 Should I run R from within Emacs?
 =====================================
 
 Yes, instead of just running it in a console, _definitely_.  As an
-alternative to other IDE's such as Rstudio, _possibly_, notably if you are
-interested to use Emacs for other computer interaction.  You'd be using ESS,
+alternative to other IDE’s such as Rstudio, _possibly_, notably if you are
+interested to use Emacs for other computer interaction.  You’d be using ESS,
 Emacs Speaks Statistics, see previous FAQ.
 
    Inferior R mode provides a readline/history mechanism, object name
@@ -1480,35 +1480,35 @@
    In addition, it allows you to keep a record of your session, which can
 also be used for error recovery through the use of the transcript mode.
 
-   To specify command line arguments for the inferior R process, use 'C-u
-M-x R' for starting R.
+   To specify command line arguments for the inferior R process, use ‘C-u
+M-x R’ for starting R.
 
 6.3 Debugging R from within Emacs
 =================================
 
-To debug R "from within Emacs", there are several possibilities.  To use the
+To debug R “from within Emacs”, there are several possibilities.  To use the
 Emacs GUD (Grand Unified Debugger) library with the recommended debugger
-GDB, type 'M-x gdb' and give the path to the R _binary_ as argument.  At the
-'gdb' prompt, set 'R_HOME' and other environment variables as needed (using
-e.g. 'set env R_HOME /path/to/R/', but see also below), and start the binary
-with the desired arguments (e.g., 'run --quiet').
-
-   If you have ESS, you can do 'C-u M-x R <RET> - d <SPC> g d b <RET>' to
-start an inferior R process with arguments '-d gdb'.
-
-   A third option is to start an inferior R process via ESS ('M-x R') and
-then start GUD ('M-x gdb') giving the R binary (using its full path name) as
-the program to debug.  Use the program 'ps' to find the process number of
-the currently running R process then use the 'attach' command in gdb to
+GDB, type ‘M-x gdb’ and give the path to the R _binary_ as argument.  At the
+‘gdb’ prompt, set ‘R_HOME’ and other environment variables as needed (using
+e.g. ‘set env R_HOME /path/to/R/’, but see also below), and start the binary
+with the desired arguments (e.g., ‘run --quiet’).
+
+   If you have ESS, you can do ‘C-u M-x R <RET> - d <SPC> g d b <RET>’ to
+start an inferior R process with arguments ‘-d gdb’.
+
+   A third option is to start an inferior R process via ESS (‘M-x R’) and
+then start GUD (‘M-x gdb’) giving the R binary (using its full path name) as
+the program to debug.  Use the program ‘ps’ to find the process number of
+the currently running R process then use the ‘attach’ command in gdb to
 attach it to that process.  One advantage of this method is that you have
-separate '*R*' and '*gud-gdb*' windows.  Within the '*R*' window you have
+separate ‘*R*’ and ‘*gud-gdb*’ windows.  Within the ‘*R*’ window you have
 all the ESS facilities, such as object-name completion, that we know and
 love.
 
    When using GUD mode for debugging from within Emacs, you may find it most
 convenient to use the directory with your code in it as the current working
 directory and then make a symbolic link from that directory to the R binary.
-That way '.gdbinit' can stay in the directory with the code and be used to
+That way ‘.gdbinit’ can stay in the directory with the code and be used to
 set up the environment and the search paths for the source, e.g. as follows:
 
      set env R_HOME /opt/R
@@ -1529,51 +1529,51 @@
 
      x[i] <- list(NULL)
 
-to set component 'i' of the list 'x' to 'NULL', similarly for named
-components.  Do not set 'x[i]' or 'x[[i]]' to 'NULL', because this will
+to set component ‘i’ of the list ‘x’ to ‘NULL’, similarly for named
+components.  Do not set ‘x[i]’ or ‘x[[i]]’ to ‘NULL’, because this will
 remove the corresponding component from the list.
 
-   For dropping the row names of a matrix 'x', it may be easier to use
-'rownames(x) <- NULL', similarly for column names.
+   For dropping the row names of a matrix ‘x’, it may be easier to use
+‘rownames(x) <- NULL’, similarly for column names.
 
 7.2 How can I save my workspace?
 ================================
 
-'save.image()' saves the objects in the user's '.GlobalEnv' to the file
-'.RData' in the R startup directory.  (This is also what happens after
-'q("yes")'.)  Using 'save.image(FILE)' one can save the image under a
+‘save.image()’ saves the objects in the user’s ‘.GlobalEnv’ to the file
+‘.RData’ in the R startup directory.  (This is also what happens after
+‘q("yes")’.)  Using ‘save.image(FILE)’ one can save the image under a
 different name.
 
 7.3 How can I clean up my workspace?
 ====================================
 
 To remove all objects in the currently active environment (typically
-'.GlobalEnv'), you can do
+‘.GlobalEnv’), you can do
 
      rm(list = ls(all.names = TRUE))
 
-(Without 'all = TRUE', only the objects with names not starting with a '.'
+(Without ‘all = TRUE’, only the objects with names not starting with a ‘.’
 are removed.)
 
 7.4 How can I get eval() and D() to work?
 =========================================
 
-Strange things will happen if you use 'eval(print(x), envir = e)' or 'D(x^2,
-"x")'.  The first one will either tell you that "'x'" is not found, or print
-the value of the wrong 'x'.  The other one will likely return zero if 'x'
+Strange things will happen if you use ‘eval(print(x), envir = e)’ or ‘D(x^2,
+"x")’.  The first one will either tell you that "‘x’" is not found, or print
+the value of the wrong ‘x’.  The other one will likely return zero if ‘x’
 exists, and an error otherwise.
 
    This is because in both cases, the first argument is evaluated in the
 calling environment first.  The result (which should be an object of mode
-'"expression"' or '"call"') is then evaluated or differentiated.  What you
-(most likely) really want is obtained by "quoting" the first argument upon
-surrounding it with 'expression()'.  For example,
+‘"expression"’ or ‘"call"’) is then evaluated or differentiated.  What you
+(most likely) really want is obtained by “quoting” the first argument upon
+surrounding it with ‘expression()’.  For example,
 
      R> D(expression(x^2), "x")
      2 * x
 
    Although this behavior may initially seem to be rather strange, it is
-perfectly logical.  The "intuitive" behavior could easily be implemented,
+perfectly logical.  The “intuitive” behavior could easily be implemented,
 but problems would arise whenever the expression is contained in a variable,
 passed as a parameter, or is the result of a function call.  Consider for
 instance the semantics in cases like
@@ -1585,31 +1585,31 @@
      g <- function(y) eval(substitute(y), sys.frame(sys.parent(n = 2)))
      g(a * b)
 
-   See the help page for 'deriv()' for more examples.
+   See the help page for ‘deriv()’ for more examples.
 
 7.5 Why do my matrices lose dimensions?
 =======================================
 
 When a matrix with a single row or column is created by a subscripting
-operation, e.g., 'row <- mat[2, ]', it is by default turned into a vector.
+operation, e.g., ‘row <- mat[2, ]’, it is by default turned into a vector.
 In a similar way if an array with dimension, say, 2 x 3 x 1 x 4 is created
 by subscripting it will be coerced into a 2 x 3 x 4 array, losing the
 unnecessary dimension.  After much discussion this has been determined to be
 a _feature_.
 
-   To prevent this happening, add the option 'drop = FALSE' to the
+   To prevent this happening, add the option ‘drop = FALSE’ to the
 subscripting.  For example,
 
      rowmatrix <- mat[2, , drop = FALSE]  # creates a row matrix
      colmatrix <- mat[, 2, drop = FALSE]  # creates a column matrix
      a <- b[1, 1, 1, drop = FALSE]        # creates a 1 x 1 x 1 array
 
-   The 'drop = FALSE' option should be used defensively when programming.
+   The ‘drop = FALSE’ option should be used defensively when programming.
 For example, the statement
 
      somerows <- mat[index, ]
 
-will return a vector rather than a matrix if 'index' happens to have length
+will return a vector rather than a matrix if ‘index’ happens to have length
 1, causing errors later in the code.  It should probably be rewritten as
 
      somerows <- mat[index, , drop = FALSE]
@@ -1619,25 +1619,25 @@
 
 Autoloading is rarely used since packages became lazy-loaded.
 
-   R has a special environment called '.AutoloadEnv'.  Using 'autoload(NAME,
-PKG)', where NAME and PKG are strings giving the names of an object and the
+   R has a special environment called ‘.AutoloadEnv’.  Using ‘autoload(NAME,
+PKG)’, where NAME and PKG are strings giving the names of an object and the
 package containing it, stores some information in this environment.  When R
 tries to evaluate NAME, it loads the corresponding package PKG and
-reevaluates NAME in the new package's environment.
+reevaluates NAME in the new package’s environment.
 
    Using this mechanism makes R behave as if the package was loaded, but
 does not occupy memory (yet).
 
-   See the help page for 'autoload()' for a very nice example.
+   See the help page for ‘autoload()’ for a very nice example.
 
 7.7 How should I set options?
 =============================
 
-The function 'options()' allows setting and examining a variety of global
-"options" which affect the way in which R computes and displays its results.
-The variable '.Options' holds the current values of these options, but
+The function ‘options()’ allows setting and examining a variety of global
+“options” which affect the way in which R computes and displays its results.
+The variable ‘.Options’ holds the current values of these options, but
 should never directly be assigned to unless you want to drive yourself
-crazy--simply pretend that it is a "read-only" variable.
+crazy—simply pretend that it is a “read-only” variable.
 
    For example, given
 
@@ -1657,41 +1657,41 @@
      R> test2()
      3 3.141593
 
-   What is really used is the _global_ value of '.Options', and using
-'options(OPT = VAL)' correctly updates it.  Local copies of '.Options',
-either in '.GlobalEnv' or in a function environment (frame), are just
+   What is really used is the _global_ value of ‘.Options’, and using
+‘options(OPT = VAL)’ correctly updates it.  Local copies of ‘.Options’,
+either in ‘.GlobalEnv’ or in a function environment (frame), are just
 silently disregarded.
 
 7.8 How do file names work in Windows?
 ======================================
 
-As R uses C-style string handling, '\' is treated as an escape character, so
-that for example one can enter a newline as '\n'.  When you really need a
-'\', you have to escape it with another '\'.
+As R uses C-style string handling, ‘\’ is treated as an escape character, so
+that for example one can enter a newline as ‘\n’.  When you really need a
+‘\’, you have to escape it with another ‘\’.
 
-   Thus, in filenames use something like '"c:\\data\\money.dat"'.  You can
-also replace '\' by '/' ('"c:/data/money.dat"').
+   Thus, in filenames use something like ‘"c:\\data\\money.dat"’.  You can
+also replace ‘\’ by ‘/’ (‘"c:/data/money.dat"’).
 
 7.9 Why does plotting give a color allocation error?
 ====================================================
 
 This is about a problem rarely seen with modern X11 installations.
 
-   On an X11 device, plotting sometimes, e.g., when running 'demo("image")',
-results in "Error: color allocation error".  This is an X problem, and only
+   On an X11 device, plotting sometimes, e.g., when running ‘demo("image")’,
+results in “Error: color allocation error”.  This is an X problem, and only
 indirectly related to R. It occurs when applications started prior to R have
 used all the available colors.  (How many colors are available depends on
 the X configuration; sometimes only 256 colors can be used.)
 
-   You could also set the 'colortype' of 'X11()' to '"pseudo.cube"' rather
-than the default '"pseudo"'.  See the help page for 'X11()' for more
+   You could also set the ‘colortype’ of ‘X11()’ to ‘"pseudo.cube"’ rather
+than the default ‘"pseudo"’.  See the help page for ‘X11()’ for more
 information.
 
 7.10 How do I convert factors to numeric?
 =========================================
 
 It may happen that when reading numeric data into R (usually, when reading
-in a file), they come in as factors.  If 'f' is such a factor object, you
+in a file), they come in as factors.  If ‘f’ is such a factor object, you
 can use
 
      as.numeric(as.character(f))
@@ -1700,8 +1700,8 @@
 
      as.numeric(levels(f))[as.integer(f)]
 
-   In any case, do not call 'as.numeric()' or their likes directly for the
-task at hand (as 'as.numeric()' or 'unclass()' give the internal codes).
+   In any case, do not call ‘as.numeric()’ or their likes directly for the
+task at hand (as ‘as.numeric()’ or ‘unclass()’ give the internal codes).
 
 7.11 Are Trellis displays implemented in R?
 ===========================================
@@ -1711,46 +1711,46 @@
 *grid*) provides graphical functionality that is compatible with most
 Trellis commands.
 
-   You could also look at 'coplot()' and 'dotchart()' which might do at
-least some of what you want.  Note also that the R version of 'pairs()' is
-fairly general and provides most of the functionality of 'splom()', and that
-R's default plot method has an argument 'asp' allowing to specify (and fix
+   You could also look at ‘coplot()’ and ‘dotchart()’ which might do at
+least some of what you want.  Note also that the R version of ‘pairs()’ is
+fairly general and provides most of the functionality of ‘splom()’, and that
+R’s default plot method has an argument ‘asp’ allowing to specify (and fix
 against device resizing) the aspect ratio of the plot.
 
-   (Because the word "Trellis" has been claimed as a trademark we do not use
-it in R. The name "lattice" has been chosen for the R equivalent.)
+   (Because the word “Trellis” has been claimed as a trademark we do not use
+it in R. The name “lattice” has been chosen for the R equivalent.)
 
 7.12 What are the enclosing and parent environments?
 ====================================================
 
 Inside a function you may want to access variables in two additional
-environments: the one that the function was defined in ("enclosing"), and
-the one it was invoked in ("parent").
+environments: the one that the function was defined in (“enclosing”), and
+the one it was invoked in (“parent”).
 
    If you create a function at the command line or load it in a package its
 enclosing environment is the global workspace.  If you define a function
-'f()' inside another function 'g()' its enclosing environment is the
-environment inside 'g()'.  The enclosing environment for a function is fixed
+‘f()’ inside another function ‘g()’ its enclosing environment is the
+environment inside ‘g()’.  The enclosing environment for a function is fixed
 when the function is created.  You can find out the enclosing environment
-for a function 'f()' using 'environment(f)'.
+for a function ‘f()’ using ‘environment(f)’.
 
-   The "parent" environment, on the other hand, is defined when you invoke a
-function.  If you invoke 'lm()' at the command line its parent environment
-is the global workspace, if you invoke it inside a function 'f()' then its
-parent environment is the environment inside 'f()'.  You can find out the
-parent environment for an invocation of a function by using 'parent.frame()'
-or 'sys.frame(sys.parent())'.
+   The “parent” environment, on the other hand, is defined when you invoke a
+function.  If you invoke ‘lm()’ at the command line its parent environment
+is the global workspace, if you invoke it inside a function ‘f()’ then its
+parent environment is the environment inside ‘f()’.  You can find out the
+parent environment for an invocation of a function by using ‘parent.frame()’
+or ‘sys.frame(sys.parent())’.
 
    So for most user-visible functions the enclosing environment will be the
 global workspace, since that is where most functions are defined.  The
 parent environment will be wherever the function happens to be called from.
-If a function 'f()' is defined inside another function 'g()' it will
-probably be used inside 'g()' as well, so its parent environment and
+If a function ‘f()’ is defined inside another function ‘g()’ it will
+probably be used inside ‘g()’ as well, so its parent environment and
 enclosing environment will probably be the same.
 
    Parent environments are important because things like model formulas need
 to be evaluated in the environment the function was called from, since
-that's where all the variables will be available.  This relies on the parent
+that’s where all the variables will be available.  This relies on the parent
 environment being potentially different with each invocation.
 
    Enclosing environments are important because a function can use variables
@@ -1770,34 +1770,34 @@
 ============================================
 
 Often, it is desired to use the value of an R object in a plot label, e.g.,
-a title.  This is easily accomplished using 'paste()' if the label is a
+a title.  This is easily accomplished using ‘paste()’ if the label is a
 simple character string, but not always obvious in case the label is an
 expression (for refined mathematical annotation).  In such a case, either
-use 'parse()' on your pasted character string or use 'substitute()' on an
-expression.  For example, if 'ahat' is an estimator of your parameter a of
+use ‘parse()’ on your pasted character string or use ‘substitute()’ on an
+expression.  For example, if ‘ahat’ is an estimator of your parameter a of
 interest, use
 
      title(substitute(hat(a) == ahat, list(ahat = ahat)))
 
-(note that it is '==' and not '=').  Sometimes 'bquote()' gives a more
+(note that it is ‘==’ and not ‘=’).  Sometimes ‘bquote()’ gives a more
 compact form, e.g.,
 
      title(bquote(hat(a) = .(ahat)))
 
-where subexpressions enclosed in '.()' are replaced by their values.
+where subexpressions enclosed in ‘.()’ are replaced by their values.
 
    There are more examples in the mailing list archives.
 
 7.14 What are valid names?
 ==========================
 
-When creating data frames using 'data.frame()' or 'read.table()', R by
+When creating data frames using ‘data.frame()’ or ‘read.table()’, R by
 default ensures that the variable names are syntactically valid.  (The
-argument 'check.names' to these functions controls whether variable names
-are checked and adjusted by 'make.names()' if needed.)
+argument ‘check.names’ to these functions controls whether variable names
+are checked and adjusted by ‘make.names()’ if needed.)
 
-   To understand what names are "valid", one needs to take into account that
-the term "name" is used in several different (but related) ways in the
+   To understand what names are “valid”, one needs to take into account that
+the term “name” is used in several different (but related) ways in the
 language:
 
   1. A _syntactic name_ is a string the parser interprets as this type of
@@ -1806,26 +1806,26 @@
      followed by a number.  Reserved words are not syntactic names.
   2. An _object name_ is a string associated with an object that is assigned
      in an expression either by having the object name on the left of an
-     assignment operation or as an argument to the 'assign()' function.  It
+     assignment operation or as an argument to the ‘assign()’ function.  It
      is usually a syntactic name as well, but can be any non-empty string if
-     it is quoted (and it is always quoted in the call to 'assign()').
+     it is quoted (and it is always quoted in the call to ‘assign()’).
 
   3. An _argument name_ is what appears to the left of the equals sign when
-     supplying an argument in a function call (for example, 'f(trim=.5)').
+     supplying an argument in a function call (for example, ‘f(trim=.5)’).
      Argument names are also usually syntactic names, but again can be
      anything if they are quoted.
 
   4. An _element name_ is a string that identifies a piece of an object (a
      component of a list, for example.)  When it is used on the right of the
-     '$' operator, it must be a syntactic name, or quoted.  Otherwise,
+     ‘$’ operator, it must be a syntactic name, or quoted.  Otherwise,
      element names can be any strings.  (When an object is used as a
-     database, as in a call to 'eval()' or 'attach()', the element names
+     database, as in a call to ‘eval()’ or ‘attach()’, the element names
      become object names.)
 
   5. Finally, a _file name_ is a string identifying a file in the operating
      system for reading, writing, etc.  It really has nothing much to do
      with names in the language, but it is traditional to call these strings
-     file "names".
+     file “names”.
 
 7.15 Are GAMs implemented in R?
 ===============================
@@ -1834,12 +1834,12 @@
 all the Generalized Additive Models (GAM) functionality as described in the
 GAM chapter of the White Book.  In particular, it implements backfitting
 with both local regression and smoothing splines, and is extendable.  There
-is a 'gam()' function for GAMs in package *mgcv*
+is a ‘gam()’ function for GAMs in package *mgcv*
 (https://CRAN.R-project.org/package=mgcv), but it is not an exact clone of
-what is described in the White Book (no 'lo()' for example).  Package *gss*
+what is described in the White Book (no ‘lo()’ for example).  Package *gss*
 (https://CRAN.R-project.org/package=gss) can fit spline-based GAMs too.  And
-if you can accept regression splines you can use 'glm()'.  For Gaussian GAMs
-you can use 'bruto()' from package *mda*
+if you can accept regression splines you can use ‘glm()’.  For Gaussian GAMs
+you can use ‘bruto()’ from package *mda*
 (https://CRAN.R-project.org/package=mda).
 
 7.16 Why is the output not printed when I source() a file?
@@ -1854,13 +1854,13 @@
      summary(glm(y~x+z, family=binomial))
 
 fits a logistic regression model, computes some summary information and
-returns an object of class '"summary.glm"' (*note How should I write summary
+returns an object of class ‘"summary.glm"’ (*note How should I write summary
 methods?::).
 
-   If you type '1+1' or 'summary(glm(y~x+z, family=binomial))' at the
+   If you type ‘1+1’ or ‘summary(glm(y~x+z, family=binomial))’ at the
 command line the returned value is automatically printed (unless it is
-'invisible()'), but in other circumstances, such as in a 'source()'d file or
-inside a function it isn't printed unless you specifically print it.
+‘invisible()’), but in other circumstances, such as in a ‘source()’d file or
+inside a function it isn’t printed unless you specifically print it.
 
    To print the value use
 
@@ -1870,20 +1870,20 @@
 
      print(summary(glm(y~x+z, family=binomial)))
 
-instead, or use 'source(FILE, echo=TRUE)'.
+instead, or use ‘source(FILE, echo=TRUE)’.
 
 7.17 Why does outer() behave strangely with my function?
 ========================================================
 
-As the help for 'outer()' indicates, it does not work on arbitrary functions
-the way the 'apply()' family does.  It requires functions that are
+As the help for ‘outer()’ indicates, it does not work on arbitrary functions
+the way the ‘apply()’ family does.  It requires functions that are
 vectorized to work elementwise on arrays.  As you can see by looking at the
-code, 'outer(x, y, FUN)' creates two large vectors containing every possible
-combination of elements of 'x' and 'y' and then passes this to 'FUN' all at
+code, ‘outer(x, y, FUN)’ creates two large vectors containing every possible
+combination of elements of ‘x’ and ‘y’ and then passes this to ‘FUN’ all at
 once.  Your function probably cannot handle two large vectors as parameters.
 
    If you have a function that cannot handle two vectors but can handle two
-scalars, then you can still use 'outer()' but you will need to wrap your
+scalars, then you can still use ‘outer()’ but you will need to wrap your
 function up first, to simulate vectorized behavior.  Suppose your function
 is
 
@@ -1898,47 +1898,47 @@
        sapply(seq_along(x), FUN = function(i) my.fun(x[i], y[i], ...))
      }
 
-then you can use 'outer()' by writing, e.g.,
+then you can use ‘outer()’ by writing, e.g.,
 
      outer(1:4, 1:2, FUN = wrapper, my.fun = foo, happy = 10)
 
-   Scalar functions can also be vectorized using 'Vectorize()'.
+   Scalar functions can also be vectorized using ‘Vectorize()’.
 
 7.18 Why does the output from anova() depend on the order of factors in the model?
 ==================================================================================
 
-In a model such as '~A+B+A:B', R will report the difference in sums of
-squares between the models '~1', '~A', '~A+B' and '~A+B+A:B'.  If the model
-were '~B+A+A:B', R would report differences between '~1', '~B', '~A+B', and
-'~A+B+A:B' .  In the first case the sum of squares for 'A' is comparing '~1'
-and '~A', in the second case it is comparing '~B' and '~B+A'.  In a
+In a model such as ‘~A+B+A:B’, R will report the difference in sums of
+squares between the models ‘~1’, ‘~A’, ‘~A+B’ and ‘~A+B+A:B’.  If the model
+were ‘~B+A+A:B’, R would report differences between ‘~1’, ‘~B’, ‘~A+B’, and
+‘~A+B+A:B’ .  In the first case the sum of squares for ‘A’ is comparing ‘~1’
+and ‘~A’, in the second case it is comparing ‘~B’ and ‘~B+A’.  In a
 non-orthogonal design (i.e., most unbalanced designs) these comparisons are
 (conceptually and numerically) different.
 
    Some packages report instead the sums of squares based on comparing the
 full model to the models with each factor removed one at a time (the famous
-'Type III sums of squares' from SAS, for example).  These do not depend on
+‘Type III sums of squares’ from SAS, for example).  These do not depend on
 the order of factors in the model.  The question of which set of sums of
 squares is the Right Thing provokes low-level holy wars on R-help from time
 to time.
 
    There is no need to be agitated about the particular sums of squares that
 R reports.  You can compute your favorite sums of squares quite easily.  Any
-two models can be compared with 'anova(MODEL1, MODEL2)', and 'drop1(MODEL1)'
+two models can be compared with ‘anova(MODEL1, MODEL2)’, and ‘drop1(MODEL1)’
 will show the sums of squares resulting from dropping single terms.
 
 7.19 How do I produce PNG graphics in batch mode?
 =================================================
 
-Under a Unix-like, if your installation supports the 'type="cairo"' option
-to the 'png()' device there should be no problems, and the default settings
+Under a Unix-like, if your installation supports the ‘type="cairo"’ option
+to the ‘png()’ device there should be no problems, and the default settings
 should just work.  This option is not available for versions of R prior to
-2.7.0, or without support for cairo.  From R 2.7.0 'png()' by default uses
+2.7.0, or without support for cairo.  From R 2.7.0 ‘png()’ by default uses
 the Quartz device on macOS, and that too works in batch mode.
 
-   Earlier versions of the 'png()' device used the X11 driver, which is a
+   Earlier versions of the ‘png()’ device used the X11 driver, which is a
 problem in batch mode or for remote operation.  If you have Ghostscript you
-can use 'bitmap()', which produces a PostScript or PDF file then converts it
+can use ‘bitmap()’, which produces a PostScript or PDF file then converts it
 to any bitmap format supported by Ghostscript.  On some installations this
 produces ugly output, on others it is perfectly satisfactory.  Many systems
 now come with Xvfb from X.Org (https://www.x.org/) (possibly as an optional
@@ -1950,10 +1950,10 @@
 The Unix-like command-line interface to R can only provide the inbuilt
 command line editor which allows recall, editing and re-submission of prior
 commands provided that the GNU readline library is available at the time R
-is configured for compilation.  Note that the 'development' version of
+is configured for compilation.  Note that the ‘development’ version of
 readline including the appropriate headers is needed: users of Linux binary
-distributions will need to install packages such as 'libreadline-dev'
-(Debian) or 'readline-devel' (Red Hat).
+distributions will need to install packages such as ‘libreadline-dev’
+(Debian) or ‘readline-devel’ (Red Hat).
 
 7.21 How can I turn a string into a variable?
 =============================================
@@ -1999,26 +1999,26 @@
 ==============================================
 
 The most likely reason is that you forgot to tell R to display the graph.
-Lattice functions such as 'xyplot()' create a graph object, but do not
+Lattice functions such as ‘xyplot()’ create a graph object, but do not
 display it (the same is true of *ggplot2*
 (https://CRAN.R-project.org/package=ggplot2) graphics, and Trellis graphics
-in S-PLUS).  The 'print()' method for the graph object produces the actual
+in S-PLUS).  The ‘print()’ method for the graph object produces the actual
 display.  When you use these functions interactively at the command line,
-the result is automatically printed, but in 'source()' or inside your own
-functions you will need an explicit 'print()' statement.
+the result is automatically printed, but in ‘source()’ or inside your own
+functions you will need an explicit ‘print()’ statement.
 
 7.23 How can I sort the rows of a data frame?
 =============================================
 
 To sort the rows within a data frame, with respect to the values in one or
-more of the columns, simply use 'order()' (e.g., 'DF[order(DF$a, DF[["b"]]),
-]' to sort the data frame 'DF' on columns named 'a' and 'b').
+more of the columns, simply use ‘order()’ (e.g., ‘DF[order(DF$a, DF[["b"]]),
+]’ to sort the data frame ‘DF’ on columns named ‘a’ and ‘b’).
 
 7.24 Why does the help.start() search engine not work?
 ======================================================
 
-Since R 2.10.0, the browser-based search engine in 'help.start()' is an HTML
-interface to 'help.search()', and should always work.  Before that, the
+Since R 2.10.0, the browser-based search engine in ‘help.start()’ is an HTML
+interface to ‘help.search()’, and should always work.  Before that, the
 engine utilized a Java applet.  In order for this to function properly, one
 needed a compatible version of Java installed on the system and linked to
 the browser, and both Java _and_ JavaScript enabled in the browser.
@@ -2026,7 +2026,7 @@
 7.25 Why did my .Rprofile stop working when I updated R?
 ========================================================
 
-Did you read the 'NEWS' file?  For functions that are not in the *base*
+Did you read the ‘NEWS’ file?  For functions that are not in the *base*
 package you need to specify the correct package namespace, since the code
 will be run _before_ the packages are loaded.  E.g.,
 
@@ -2038,7 +2038,7 @@
      grDevices::ps.options(horizontal = FALSE)
      utils::help.start()
 
-('graphics::ps.options(horizontal = FALSE)' in R 1.9.x).
+(‘graphics::ps.options(horizontal = FALSE)’ in R 1.9.x).
 
 7.26 Where have all the methods gone?
 =====================================
@@ -2047,20 +2047,20 @@
 has the advantage that they cannot be called inadvertently with arguments of
 the wrong class, but it makes them harder to view.
 
-   To see the code for an S3 method (e.g., '[.terms') use
+   To see the code for an S3 method (e.g., ‘[.terms’) use
 
      getS3method("[", "terms")
 
-To see the code for an unexported function 'foo()' in the namespace of
-package '"bar"' use 'bar:::foo'.  Don't use these constructions to call
-unexported functions in your own code--they are probably unexported for a
+To see the code for an unexported function ‘foo()’ in the namespace of
+package ‘"bar"’ use ‘bar:::foo’.  Don’t use these constructions to call
+unexported functions in your own code—they are probably unexported for a
 reason and may change without warning.
 
 7.27 How can I create rotated axis labels?
 ==========================================
 
-To rotate axis labels (using base graphics), you need to use 'text()',
-rather than 'mtext()', as the latter does not support 'par("srt")'.
+To rotate axis labels (using base graphics), you need to use ‘text()’,
+rather than ‘mtext()’, as the latter does not support ‘par("srt")’.
 
      ## Increase bottom margin to make room for rotated labels
      par(mar = c(7, 4, 4, 2) + 0.1)
@@ -2076,50 +2076,50 @@
      ## Plot x axis label at line 6 (of 7)
      mtext(1, text = "X Axis Label", line = 6)
 
-When plotting the x axis labels, we use 'srt = 45' for text rotation angle,
-'adj = 1' to place the right end of text at the tick marks, and 'xpd = TRUE'
+When plotting the x axis labels, we use ‘srt = 45’ for text rotation angle,
+‘adj = 1’ to place the right end of text at the tick marks, and ‘xpd = TRUE’
 to allow for text outside the plot region.  You can adjust the value of the
-'0.25' offset as required to move the axis labels up or down relative to the
-x axis.  See '?par' for more information.
+‘0.25’ offset as required to move the axis labels up or down relative to the
+x axis.  See ‘?par’ for more information.
 
    Also see Figure 1 and associated code in Paul Murrell (2003),
-"Integrating grid Graphics Output with Base Graphics Output", _R News_,
-*3/2*, 7-12.
+“Integrating grid Graphics Output with Base Graphics Output”, _R News_,
+*3/2*, 7–12.
 
 7.28 Why is read.table() so inefficient?
 ========================================
 
-By default, 'read.table()' needs to read in everything as character data,
+By default, ‘read.table()’ needs to read in everything as character data,
 and then try to figure out which variables to convert to numerics or
 factors.  For a large data set, this takes considerable amounts of time and
-memory.  Performance can substantially be improved by using the 'colClasses'
+memory.  Performance can substantially be improved by using the ‘colClasses’
 argument to specify the classes to be assumed for the columns of the table.
 
 7.29 What is the difference between package and library?
 ========================================================
 
-A "package" is a standardized collection of material extending R, e.g.
-providing code, data, or documentation.  A "library" is a place (directory)
-where R knows to find packages it can use (i.e., which were "installed").  R
-is told to use a package (to "load" it and add it to the search path) via
-calls to the function 'library'.  I.e., 'library()' is employed to load a
+A “package” is a standardized collection of material extending R, e.g.
+providing code, data, or documentation.  A “library” is a place (directory)
+where R knows to find packages it can use (i.e., which were “installed”).  R
+is told to use a package (to “load” it and add it to the search path) via
+calls to the function ‘library’.  I.e., ‘library()’ is employed to load a
 package from libraries containing packages.
 
    *Note R Add-On Packages::, for more details.  See also Uwe Ligges (2003),
-"R Help Desk: Package Management", _R News_, *3/3*, 37-39.
+“R Help Desk: Package Management”, _R News_, *3/3*, 37–39.
 
 7.30 I installed a package but the functions are not there
 ==========================================================
 
-To actually _use_ the package, it needs to be _loaded_ using 'library()'.
+To actually _use_ the package, it needs to be _loaded_ using ‘library()’.
 
    See *note R Add-On Packages:: and *note What is the difference between
 package and library?:: for more information.
 
-7.31 Why doesn't R think these numbers are equal?
+7.31 Why doesn’t R think these numbers are equal?
 =================================================
 
-The only numbers that can be represented exactly in R's numeric type are
+The only numbers that can be represented exactly in R’s numeric type are
 integers and fractions whose denominator is a power of 2.  All other numbers
 are internally rounded to (typically) 53 binary digits accuracy.  As a
 result, two floating point numbers will not reliably be equal unless they
@@ -2134,20 +2134,20 @@
      R> print(a * a, digits = 18)
      [1] 2.00000000000000044
 
-   The function 'all.equal()' compares two objects using a numeric tolerance
-of '.Machine$double.eps ^ 0.5'.  If you want much greater accuracy than this
+   The function ‘all.equal()’ compares two objects using a numeric tolerance
+of ‘.Machine$double.eps ^ 0.5’.  If you want much greater accuracy than this
 you will need to consider error propagation carefully.
 
    A discussion with many easily followed examples is in Appendix G
-"Computational Precision and Floating Point Arithmetic", pages 753-771 of
+“Computational Precision and Floating Point Arithmetic”, pages 753–771 of
 _Statistical Analysis and Data Display: An Intermediate Course with Examples
 in R_, Richard M. Heiberger and Burt Holland (Springer 2015, second
 edition).  This appendix is a free download from
 <https://link.springer.com/content/pdf/bbm:978-1-4939-2122-5/1.pdf>.
 
-   For more information, see e.g. David Goldberg (1991), "What Every
-Computer Scientist Should Know About Floating-Point Arithmetic", _ACM
-Computing Surveys_, *23/1*, 5-48, also available via
+   For more information, see e.g. David Goldberg (1991), “What Every
+Computer Scientist Should Know About Floating-Point Arithmetic”, _ACM
+Computing Surveys_, *23/1*, 5–48, also available via
 <https://docs.oracle.com/cd/E19957-01/806-3568/ncg_goldberg.html>.
 
    Here is another example, this time using addition:
@@ -2166,15 +2166,15 @@
 7.32 How can I capture or ignore errors in a long simulation?
 =============================================================
 
-Use 'try()', which returns an object of class '"try-error"' instead of an
-error, or preferably 'tryCatch()', where the return value can be configured
+Use ‘try()’, which returns an object of class ‘"try-error"’ instead of an
+error, or preferably ‘tryCatch()’, where the return value can be configured
 more flexibly.  For example
 
      beta[i,] <- tryCatch(coef(lm(formula, data)),
                           error = function(e) rep(NaN, 4))
 
-would return the coefficients if the 'lm()' call succeeded and would return
-'c(NaN, NaN, NaN, NaN)' if it failed (presumably there are supposed to be 4
+would return the coefficients if the ‘lm()’ call succeeded and would return
+‘c(NaN, NaN, NaN, NaN)’ if it failed (presumably there are supposed to be 4
 coefficients in this example).
 
 7.33 Why are powers of negative numbers wrong?
@@ -2192,7 +2192,7 @@
 
 to get the square of -2.
 
-   The precedence rules are documented in '?Syntax', and to see how R
+   The precedence rules are documented in ‘?Syntax’, and to see how R
 interprets an expression you can look at the parse tree
 
      R> as.list(quote(-2^2))
@@ -2205,10 +2205,10 @@
 7.34 How can I save the result of each iteration in a loop into a separate file?
 ================================================================================
 
-One way is to use 'paste()' (or 'sprintf()') to concatenate a stem filename
-and the iteration number while 'file.path()' constructs the path.  For
-example, to save results into files 'result1.rda', ..., 'result100.rda' in
-the subdirectory 'Results' of the current working directory, one can use
+One way is to use ‘paste()’ (or ‘sprintf()’) to concatenate a stem filename
+and the iteration number while ‘file.path()’ constructs the path.  For
+example, to save results into files ‘result1.rda’, ..., ‘result100.rda’ in
+the subdirectory ‘Results’ of the current working directory, one can use
 
      for(i in 1:100) {
        ## Calculations constructing "some_object" ...
@@ -2226,10 +2226,10 @@
 7.36 Why are there unwanted borders, lines or grid-like artifacts when viewing a plot saved to a PS or PDF file?
 ================================================================================================================
 
-This can occur when using functions such as 'polygon()', 'filled.contour()',
-'image()' or other functions which may call these internally.  In the case
-of 'polygon()', you may observe unwanted borders between the polygons even
-when setting the 'border' argument to 'NA' or '"transparent"'.
+This can occur when using functions such as ‘polygon()’, ‘filled.contour()’,
+‘image()’ or other functions which may call these internally.  In the case
+of ‘polygon()’, you may observe unwanted borders between the polygons even
+when setting the ‘border’ argument to ‘NA’ or ‘"transparent"’.
 
    The source of the problem is the PS/PDF viewer when the plot is
 anti-aliased.  The details for the solution will be different depending upon
@@ -2255,7 +2255,7 @@
      From a console command line, use:
           $ kwriteconfig --file okularpartrc --group 'Dlg Performance' \
                          --key GraphicsAntialias Disabled
-     Then restart Okular.  Change the final word to 'Enabled' to restore the
+     Then restart Okular.  Change the final word to ‘Enabled’ to restore the
      original setting.
 
 7.37 Why does backslash behave strangely inside strings?
@@ -2263,7 +2263,7 @@
 
 This question most often comes up in relation to file names (see *note How
 do file names work in Windows?::) but it also happens that people complain
-that they cannot seem to put a single '\' character into a text string
+that they cannot seem to put a single ‘\’ character into a text string
 unless it happens to be followed by certain other characters.
 
    To understand this, you have to distinguish between character strings and
@@ -2278,10 +2278,10 @@
      > cat(str, "\n")
      This "text" is quoted
 
-The _escape sequences_ '\"' and '\n' represent a double quote and the
-newline character respectively.  Printing text strings, using 'print()' or
+The _escape sequences_ ‘\"’ and ‘\n’ represent a double quote and the
+newline character respectively.  Printing text strings, using ‘print()’ or
 by typing the name at the prompt will use the escape sequences too, but the
-'cat()' function will display the string as-is.  Notice that '"\n"' is a
+‘cat()’ function will display the string as-is.  Notice that ‘"\n"’ is a
 one-character string, not two; the backslash is not actually in the string,
 it is just generated in the printed representation.
 
@@ -2301,37 +2301,37 @@
 mechanism.  In those cases you may need a _quadruple_ backslash to represent
 a single literal one.
 
-   In versions of R up to 2.4.1 an unknown escape sequence like '\p' was
-quietly interpreted as just 'p'.  Current versions of R emit a warning.
+   In versions of R up to 2.4.1 an unknown escape sequence like ‘\p’ was
+quietly interpreted as just ‘p’.  Current versions of R emit a warning.
 
 7.38 How can I put error bars or confidence bands on my plot?
 =============================================================
 
 Some functions will display a particular kind of plot with error bars, such
-as the 'bar.err()' function in the *agricolae*
-(https://CRAN.R-project.org/package=agricolae) package, the 'plotCI()'
+as the ‘bar.err()’ function in the *agricolae*
+(https://CRAN.R-project.org/package=agricolae) package, the ‘plotCI()’
 function in the *gplots* (https://CRAN.R-project.org/package=gplots)
-package, the 'plotCI()' and 'brkdn.plot()' functions in the *plotrix*
-(https://CRAN.R-project.org/package=plotrix) package and the 'error.bars()',
-'error.crosses()' and 'error.bars.by()' functions in the *psych*
+package, the ‘plotCI()’ and ‘brkdn.plot()’ functions in the *plotrix*
+(https://CRAN.R-project.org/package=plotrix) package and the ‘error.bars()’,
+‘error.crosses()’ and ‘error.bars.by()’ functions in the *psych*
 (https://CRAN.R-project.org/package=psych) package.  Within these types of
-functions, some will accept the measures of dispersion (e.g., 'plotCI'),
-some will calculate the dispersion measures from the raw values ('bar.err',
-'brkdn.plot'), and some will do both ('error.bars').  Still other functions
+functions, some will accept the measures of dispersion (e.g., ‘plotCI’),
+some will calculate the dispersion measures from the raw values (‘bar.err’,
+‘brkdn.plot’), and some will do both (‘error.bars’).  Still other functions
 will just display error bars, like the dispersion function in the *plotrix*
 (https://CRAN.R-project.org/package=plotrix) package.  Most of the above
-functions use the 'arrows()' function in the base *graphics* package to draw
+functions use the ‘arrows()’ function in the base *graphics* package to draw
 the error bars.
 
    The above functions all use the base graphics system.  The grid and
 lattice graphics systems also have specific functions for displaying error
-bars, e.g., the 'grid.arrow()' function in the *grid* package, and the
-'geom_errorbar()', 'geom_errorbarh()', 'geom_pointrange()',
-'geom_linerange()', 'geom_crossbar()' and 'geom_ribbon()' functions in the
+bars, e.g., the ‘grid.arrow()’ function in the *grid* package, and the
+‘geom_errorbar()’, ‘geom_errorbarh()’, ‘geom_pointrange()’,
+‘geom_linerange()’, ‘geom_crossbar()’ and ‘geom_ribbon()’ functions in the
 *ggplot2* (https://CRAN.R-project.org/package=ggplot2) package.  In the
-lattice system, error bars can be displayed with 'Dotplot()' or 'xYplot()'
+lattice system, error bars can be displayed with ‘Dotplot()’ or ‘xYplot()’
 in the *Hmisc* (https://CRAN.R-project.org/package=Hmisc) package and
-'segplot()' in the *latticeExtra*
+‘segplot()’ in the *latticeExtra*
 (https://CRAN.R-project.org/package=latticeExtra) package.
 
 7.39 How do I create a plot with two y-axes?
@@ -2341,9 +2341,9 @@
 scaled to the same vertical size and showing separate vertical axes on the
 left and right sides of the plot that reflect the original scales of the
 data, is possible in R but is not recommended.  The basic approach for
-constructing such graphs is to use 'par(new=TRUE)' (see '?par'); functions
-'twoord.plot()' (in the *plotrix*
-(https://CRAN.R-project.org/package=plotrix) package) and 'doubleYScale()'
+constructing such graphs is to use ‘par(new=TRUE)’ (see ‘?par’); functions
+‘twoord.plot()’ (in the *plotrix*
+(https://CRAN.R-project.org/package=plotrix) package) and ‘doubleYScale()’
 (in the *latticeExtra* (https://CRAN.R-project.org/package=latticeExtra)
 package) automate the process somewhat.
 
@@ -2352,43 +2352,43 @@
 
 In most cases, typing the name of the function will print its source code.
 However, code is sometimes hidden in a namespace, or compiled.  For a
-complete overview on how to access source code, see Uwe Ligges (2006), "Help
-Desk: Accessing the sources", _R News_, *6/4*, 43-45
+complete overview on how to access source code, see Uwe Ligges (2006), “Help
+Desk: Accessing the sources”, _R News_, *6/4*, 43–45
 (<https://CRAN.R-project.org/doc/Rnews/Rnews_2006-4.pdf>).
 
 7.41 Why does summary() report strange results for the R^2 estimate when I fit a linear model with no intercept?
 ================================================================================================================
 
-As described in '?summary.lm', when the intercept is zero (e.g., from 'y ~ x
-- 1' or 'y ~ x + 0'), 'summary.lm()' uses the formula R^2 = 1 - Sum(R[i]^2)
+As described in ‘?summary.lm’, when the intercept is zero (e.g., from ‘y ~ x
+- 1’ or ‘y ~ x + 0’), ‘summary.lm()’ uses the formula R^2 = 1 - Sum(R[i]^2)
 / Sum((y[i])^2) which is different from the usual R^2 = 1 - Sum(R[i]^2) /
 Sum((y[i] - mean(y))^2).  There are several reasons for this:
-   * Otherwise the R^2 could be negative (because the model with zero
+   • Otherwise the R^2 could be negative (because the model with zero
      intercept can fit _worse_ than the constant-mean model it is implicitly
      compared to).
-   * If you set the slope to zero in the model with a line through the
+   • If you set the slope to zero in the model with a line through the
      origin you get fitted values y*=0
-   * The model with constant, non-zero mean is not nested in the model with
+   • The model with constant, non-zero mean is not nested in the model with
      a line through the origin.
 
    All these come down to saying that if you know _a priori_ that E[Y]=0
-when x=0 then the 'null' model that you should compare to the fitted line,
-the model where x doesn't explain any of the variance, is the model where
-E[Y]=0 everywhere.  (If you don't know a priori that E[Y]=0 when x=0, then
-you probably shouldn't be fitting a line through the origin.)
+when x=0 then the ‘null’ model that you should compare to the fitted line,
+the model where x doesn’t explain any of the variance, is the model where
+E[Y]=0 everywhere.  (If you don’t know a priori that E[Y]=0 when x=0, then
+you probably shouldn’t be fitting a line through the origin.)
 
 7.42 Why is R apparently not releasing memory?
 ==============================================
 
-This question is often asked in different flavors along the lines of "I have
-removed objects in R and run 'gc()' and yet 'ps'/'top' still shows the R
-process using a lot of memory", often on Linux machines.
+This question is often asked in different flavors along the lines of “I have
+removed objects in R and run ‘gc()’ and yet ‘ps’/‘top’ still shows the R
+process using a lot of memory”, often on Linux machines.
 
    This is an artifact of the way the operating system (OS) allocates
 memory.  In general it is common that the OS is not capable of releasing all
 unused memory.  In extreme cases it is possible that even if R frees almost
 all its memory, the OS can not release any of it due to its design and thus
-tools such as 'ps' or 'top' will report substantial amount of resident RAM
+tools such as ‘ps’ or ‘top’ will report substantial amount of resident RAM
 used by the R process even though R has released all that memory.  In
 general such tools do _not_ report the actual memory usage of the process
 but rather what the OS is reserving for that process.
@@ -2400,15 +2400,15 @@
 this happens.
 
    Most systems use two separate ways to allocate memory.  For allocation of
-large chunks they will use 'mmap' to map memory into the process address
+large chunks they will use ‘mmap’ to map memory into the process address
 space.  Such chunks can be released immediately when they are completely
 free, because they can reside anywhere in the virtual memory.  However, this
 is a relatively expensive operation and many OSes have a limit on the number
 of such allocated chunks, so this is only used for allocating large memory
 regions.  For smaller allocations the system can expand the data segment of
-the process (historically using the 'brk' system call), but this whole area
+the process (historically using the ‘brk’ system call), but this whole area
 is always contiguous.  The OS can only move the end of this space, it cannot
-create any "holes".  Since this operation is fairly cheap, it is used for
+create any “holes”.  Since this operation is fairly cheap, it is used for
 allocations of small pieces of memory.  However, the side-effect is that
 even if there is just one byte that is in use at the end of the data
 segment, the OS cannot release any memory at all, because it cannot change
@@ -2421,9 +2421,9 @@
 unused portions of the virtual memory so it does not necessarily reduce the
 amount of real memory available for other applications.  Typically, small
 objects such as strings or pairlists will be affected by this behavior,
-whereas large objects such as long vectors will be allocated using 'mmap'
+whereas large objects such as long vectors will be allocated using ‘mmap’
 and thus not affected.  On Linux (and possibly other Unix-like systems) it
-is possible to use the 'mallinfo' system call (also see the mallinfo
+is possible to use the ‘mallinfo’ system call (also see the mallinfo
 (https://rforge.net/mallinfo) package) to query the allocator about the
 layout of the allocations, including the actually used memory as well as
 unused memory that cannot be released.
@@ -2431,12 +2431,12 @@
 7.43 How can I enable secure https downloads in R?
 ==================================================
 
-From R 4.2.0, '"libcurl"' download method is always available and used for
+From R 4.2.0, ‘"libcurl"’ download method is always available and used for
 HTTPS by default on all platforms.  It has been used since R 3.3.0
-everywhere but Windows where the default method '"wininet"' also supported
+everywhere but Windows where the default method ‘"wininet"’ also supported
 HTTPS.
 
-   So nothing needs to be done to access 'https://' websites in recent
+   So nothing needs to be done to access ‘https://’ websites in recent
 versions of R.
 
 7.44 How can I get CRAN package binaries for outdated versions of R?
@@ -2445,13 +2445,13 @@
 Since March 2016, Windows and macOS binaries of CRAN packages for old
 versions of R (released more than 5 years ago) are made available from a
 central CRAN archive server instead of the CRAN mirrors.  To get these, one
-should set the CRAN "mirror" element of the 'repos' option accordingly, by
+should set the CRAN “mirror” element of the ‘repos’ option accordingly, by
 something like
      local({r <- getOption("repos")
             r["CRAN"] <- "http://CRAN-archive.R-project.org"
             options(repos = r)
            })
-(see '?options' for more information).
+(see ‘?options’ for more information).
 
 8 R Programming
 ***************
@@ -2459,14 +2459,14 @@
 8.1 How should I write summary methods?
 =======================================
 
-Suppose you want to provide a summary method for class '"foo"'.  Then
-'summary.foo()' should not print anything, but return an object of class
-'"summary.foo"', _and_ you should write a method 'print.summary.foo()' which
+Suppose you want to provide a summary method for class ‘"foo"’.  Then
+‘summary.foo()’ should not print anything, but return an object of class
+‘"summary.foo"’, _and_ you should write a method ‘print.summary.foo()’ which
 nicely prints the summary information and invisibly returns its object.
-This approach is preferred over having 'summary.foo()' print summary
+This approach is preferred over having ‘summary.foo()’ print summary
 information and return something useful, as sometimes you need to grab
-something computed by 'summary()' inside a function or similar.  In such
-cases you don't want anything printed.
+something computed by ‘summary()’ inside a function or similar.  In such
+cases you don’t want anything printed.
 
 8.2 How can I debug dynamically loaded code?
 ============================================
@@ -2474,35 +2474,35 @@
 Roughly speaking, you need to start R inside the debugger, load the code,
 send an interrupt, and then set the required breakpoints.
 
-   See section "Finding entry points in dynamically loaded code" in 'Writing
-R Extensions'.  This manual is included in the R distribution, *note What
+   See section “Finding entry points in dynamically loaded code” in ‘Writing
+R Extensions’.  This manual is included in the R distribution, *note What
 documentation exists for R?::.
 
 8.3 How can I inspect R objects when debugging?
 ===============================================
 
-The most convenient way is to call 'R_PV' from the symbolic debugger.
+The most convenient way is to call ‘R_PV’ from the symbolic debugger.
 
-   See section "Inspecting R objects when debugging" in 'Writing R
-Extensions'.
+   See section “Inspecting R objects when debugging” in ‘Writing R
+Extensions’.
 
 8.4 How can I change compilation flags?
 =======================================
 
-Suppose you have C code file for dynloading into R, but you want to use 'R
-CMD SHLIB' with compilation flags other than the default ones (which were
+Suppose you have C code file for dynloading into R, but you want to use ‘R
+CMD SHLIB’ with compilation flags other than the default ones (which were
 determined when R was built).
 
    Starting with R 2.1.0, users can provide personal Makevars configuration
-files in '$HOME/.R' to override the default flags.  See section "Add-on
-packages" in 'R Installation and Administration'.
+files in ‘$HOME/.R’ to override the default flags.  See section “Add-on
+packages” in ‘R Installation and Administration’.
 
 8.5 How can I debug S4 methods?
 ===============================
 
-Use the 'trace()' function with argument 'signature=' to add calls to the
+Use the ‘trace()’ function with argument ‘signature=’ to add calls to the
 browser or any other code to the method that will be dispatched for the
-corresponding signature.  See '?trace' for details.
+corresponding signature.  See ‘?trace’ for details.
 
 9 R Bugs
 ********
@@ -2512,31 +2512,31 @@
 
 If R executes an illegal instruction, or dies with an operating system error
 message that indicates a problem in the program (as opposed to something
-like "disk full"), then it is certainly a bug.  If you call '.C()',
-'.Fortran()', '.External()' or '.Call()' (or '.Internal()') yourself (or in
+like “disk full”), then it is certainly a bug.  If you call ‘.C()’,
+‘.Fortran()’, ‘.External()’ or ‘.Call()’ (or ‘.Internal()’) yourself (or in
 a function you wrote), you can always crash R by using wrong argument types
 (modes).  This is not a bug.
 
    Taking forever to complete a command can be a bug, but you must make
-certain that it was really R's fault.  Some commands simply take a long
+certain that it was really R’s fault.  Some commands simply take a long
 time.  If the input was such that you _know_ it should have been processed
-quickly, report a bug.  If you don't know whether the command should take a
+quickly, report a bug.  If you don’t know whether the command should take a
 long time, find out by looking in the manual or by asking for assistance.
 
    If a command you are familiar with causes an R error message in a case
 where its usual definition ought to be reasonable, it is probably a bug.  If
 a command does the wrong thing, that is a bug.  But be sure you know for
-certain what it ought to have done.  If you aren't familiar with the
-command, or don't know for certain how the command is supposed to work, then
+certain what it ought to have done.  If you aren’t familiar with the
+command, or don’t know for certain how the command is supposed to work, then
 it might actually be working right.  For example, people sometimes think
-there is a bug in R's mathematics because they don't understand how
+there is a bug in R’s mathematics because they don’t understand how
 finite-precision arithmetic works.  Rather than jumping to conclusions, show
 the problem to someone who knows for certain.  Unexpected results of
-comparison of decimal numbers, for example '0.28 * 100 != 28' or '0.1 + 0.2
-!= 0.3', are not a bug.  *Note Why doesn't R think these numbers are
+comparison of decimal numbers, for example ‘0.28 * 100 != 28’ or ‘0.1 + 0.2
+!= 0.3’, are not a bug.  *Note Why doesn't R think these numbers are
 equal?::, for more details.
 
-   Finally, a command's intended definition may not be best for statistical
+   Finally, a command’s intended definition may not be best for statistical
 analysis.  This is a very important sort of problem, but it is also a matter
 of judgment.  Also, it is easy to come to such a conclusion out of ignorance
 of some of the existing features.  It is probably best not to complain about
@@ -2544,15 +2544,15 @@
 feel confident that you understand it, and know for certain that what you
 want is not available.  If you are not sure what the command is supposed to
 do after a careful reading of the manual this indicates a bug in the manual.
-The manual's job is to make everything clear.  It is just as important to
+The manual’s job is to make everything clear.  It is just as important to
 report documentation bugs as program bugs.  However, we know that the
-introductory documentation is seriously inadequate, so you don't need to
+introductory documentation is seriously inadequate, so you don’t need to
 report this.
 
    If the online argument list of a function disagrees with the manual, one
 of them must be wrong, so report the bug.
 
-   See also "Making sure it's a bug" in Bug Reporting in R
+   See also “Making sure it’s a bug” in Bug Reporting in R
 (https://www.r-project.org/bugs.html) for more information.
 
 9.2 How to report a bug
@@ -2562,7 +2562,7 @@
 report it in a way which is useful.  What is most useful is an exact
 description of what commands you type, starting with the shell command to
 run R, until the problem happens.  Always include the version of R, machine,
-and operating system that you are using; type 'version' in R to print this.
+and operating system that you are using; type ‘version’ in R to print this.
 
    The most important principle in reporting a bug is to report _facts_, not
 hypotheses or categorizations.  It is always easier to report the facts, but
@@ -2578,16 +2578,16 @@
 
      R> data.frame(x, y, z, monday, tuesday)
 
-never returns.  Do not report that 'data.frame()' fails for large data sets.
+never returns.  Do not report that ‘data.frame()’ fails for large data sets.
 Perhaps it fails when a variable name is a day of the week.  If this is so
-then when others got your report they would try out the 'data.frame()'
+then when others got your report they would try out the ‘data.frame()’
 command on a large data set, probably with no day of the week variable name,
 and not see any problem.  There is no way in the world that others could
 guess that they should try a day of the week variable name.
 
    Or perhaps the command fails because the last command you used was a
-method for '"["()' that had a bug causing R's internal data structures to be
-corrupted and making the 'data.frame()' command fail from then on.  This is
+method for ‘"["()’ that had a bug causing R’s internal data structures to be
+corrupted and making the ‘data.frame()’ command fail from then on.  This is
 why others need to know what other commands you have typed (or read from
 your startup file).
 
@@ -2600,12 +2600,12 @@
 <https://en.wikipedia.org/wiki/Reproducibility>) the problem, preferably the
 simplest one you have found.
 
-   Invoking R with the '--vanilla' option may help in isolating a bug.  This
+   Invoking R with the ‘--vanilla’ option may help in isolating a bug.  This
 ensures that the site profile and saved data files are not read.
 
    Before you actually submit a bug report, you should check whether the bug
-has already been reported and/or fixed.  First, try the "Show open bugs
-new-to-old" or the search facility on <https://bugs.R-project.org/>.
+has already been reported and/or fixed.  First, try the “Show open bugs
+new-to-old” or the search facility on <https://bugs.R-project.org/>.
 Second, consult <https://svn.R-project.org/R/trunk/doc/NEWS.Rd>, which
 records changes that will appear in the _next_ release of R, including bug
 fixes that do not appear on the Bug Tracker.  Third, if possible try the
@@ -2616,25 +2616,25 @@
 maintainer, and only submitted to the R-bugs repository by package
 maintainers, mentioning the package in the subject line.
 
-   A bug report can be generated using the function 'bug.report()'.  For
+   A bug report can be generated using the function ‘bug.report()’.  For
 reports on R this will open the R Bugzilla page at
 <https://bugs.R-project.org/>: for a contributed package it will open the
-package's bug tracker Web page or help you compose an email to the
-maintainer.  Since 2016, only "members" (including all who have previously
-submitted bugs) can submit new bugs on the R Bugzilla.  See "Where to submit
-bug reports and patches" on Bug Reporting in R
+package’s bug tracker Web page or help you compose an email to the
+maintainer.  Since 2016, only “members” (including all who have previously
+submitted bugs) can submit new bugs on the R Bugzilla.  See “Where to submit
+bug reports and patches” on Bug Reporting in R
 (https://www.r-project.org/bugs.html) for more information.
 
    There is a section of the bug repository for suggestions for enhancements
-for R labelled 'wishlist'.  Suggestions can be submitted in the same ways as
+for R labelled ‘wishlist’.  Suggestions can be submitted in the same ways as
 bugs, but please ensure that the subject line makes clear that this is for
-the wishlist and not a bug report, for example by starting with 'Wishlist:'.
+the wishlist and not a bug report, for example by starting with ‘Wishlist:’.
 
    Comments on and suggestions for the Windows port of R should be sent to
 <R-windows@R-project.org>.
 
    Corrections to and comments on message translations should be sent to the
-last translator (listed at the top of the appropriate '.po' file) or to the
+last translator (listed at the top of the appropriate ‘.po’ file) or to the
 translation team as listed at
 <https://developer.R-project.org/TranslationTeams.html>.
 
diff -ru -P -x .mirror -x ls_lR -x Old R-release-orig/doc/NEWS R-patched/doc/NEWS
--- R-release-orig/doc/NEWS	2023-10-31 09:05:18.000000000 +0100
+++ R-patched/doc/NEWS	2024-02-11 01:35:35.361765609 +0100
@@ -1,5 +1,83 @@
 R News
 
+CHANGES IN R 4.3.2 patched:
+
+  NEW FEATURES:
+
+    * iconv() now fixes up variant encoding names such as "utf8"
+      case-insensitively.
+
+  DEPRECATED AND DEFUNCT:
+
+    * The legacy encoding = "MacRoman" is deprecated in pdf() and
+      postscript(): support was incomplete in earlier versions of R.
+
+  BUG FIXES:
+
+    * Arguments are now properly forwarded to methods on S4 generics
+      with ... in the middle of their formal arguments. This was broken
+      for the case when a method introduced an argument but did not
+      include ... in its own formals. Thanks to Herv? Pag?s for the
+      report PR#18538.
+
+    * Some invalid file arguments to pictex(), postscript() and xfig()
+      opened a file called NA rather than throw an error.  These
+      included postscript(NULL) (which some people expected to work
+      like pdf(NULL)).
+
+    * Passing filename = NA to svg(), cairo_pdf(), cairo_ps() or the
+      Cairo-based bitmap devices opened a file called NA: it now throws
+      an error.
+
+    * quartz(file = NA) opened a file called NA, including when used as
+      a Quartz-based bitmap device.  It now gives an error.
+
+    * rank(<long vector>) now works, fixing PR#18617, thanks to Ilia
+      Kats.
+
+    * seq.int() did not adequately check its length.out argument.
+
+    * match(<POSIXct>, .) is correct again for differing time zones,
+      ditto for "POSIXlt", fixing PR#18618 reported by Bastian Klein.
+
+    * drop.terms(*, dropx = <0-length>) now works, fixing PR#18563 as
+      proposed by Mikael Jagan.
+
+    * drop.terms(*) keeps + offset(.) terms when it should, PR#18565,
+      and drop.terms() no longer makes up a response, PR#18566, fixing
+      both bugs thanks to Mikael Jagan.
+
+    * getS3method("t", "test") no longer finds the t.test() function,
+      fixing PR#18627.
+
+    * pdf() and postscript() support for the documented Adobe encodings
+      "Greek" and "Cyrilllic" was missing (although the corresponding
+      Windows' codepages could be used).
+
+    * Computations of glyph metric information for pdf() and
+      postscript() did not take into account that transliteration could
+      replace one character by two or more (only seen on macOS 14) and
+      typically warned that the information was not known.
+
+    * rank(x) no longer overflows during integer addition, when
+      computing rank average for largish but not-yet long vector x,
+      fixing PR#18630, thanks to Ilia Kats.
+
+    * list.files() on Windows now returns also files with names longer
+      that 260 bytes (the Windows limit is 260 characters).
+      Previously, some file names particularly with 'East Asian'
+      characters were omitted.
+
+    * cov2cor(<0 x 0>) now works, fixing PR#18423 thanks to Mikael
+      Jagan and Elin Warning.
+
+    * cov2cor(<negative diagonal>) and similar now give one warning
+      instead of two, with better wording, fixing PR#18424 thanks to
+      Mikael Jagan.
+
+    * tools:: startDynamicHelp() now ensures port is in proper range,
+      fixing PR#18645.
+
 CHANGES IN R 4.3.2:
 
   NEW FEATURES:
@@ -118,7 +196,7 @@
       fixing PR#18515 reported and diagnosed by Stephen Wade.
 
     * The C prototypes for LAPACK calls dspgv and dtptrs in
-      R_exts/Lapack.h had one too many and one too few character length
+      R_ext/Lapack.h had one too many and one too few character length
       arguments - but this has not caused any known issues. To get the
       corrected prototypes, include
 
@@ -126,7 +204,7 @@
               #ifdef PR18534fixed
               # define usePR18534fix 1
               #endif
-              #include <R_exts/Lapack.h>
+              #include <R_ext/Lapack.h>
       
       in your C/C++ code (PR#18534).
 
@@ -560,7 +638,7 @@
     * USE_FC_LEN_T is the default: this uses the correct
       (compiler-dependent) prototypes for Fortran BLAS/LAPACK routines
       called from C/C++, and requires adjustment of many such calls -
-      see 'Writing R Extensions' SS6.6.1.
+      see 'Writing R Extensions' ?6.6.1.
 
     * There is initial support for C++23 as several compilers are now
       supporting -std=c++23 or -std=c++2b or similar.  As for C++20,
@@ -602,7 +680,7 @@
       the package's DESCRIPTION file or _via_ options --use-C17 and so
       on of R CMD INSTALL and R CMD SHLIB.
 
-      For further details see "Writing R Extensions" SS1.2.5.
+      For further details see "Writing R Extensions" ?1.2.5.
 
     * (Windows) A src/Makefile.ucrt or src/Makefile.win file is now
       included after R_HOME/etcR_ARCH/Makeconf and so no longer needs
@@ -612,7 +690,7 @@
 
     * configure is now passed crucial variables such as CC and CFLAGS
       in its environment, as many packages were not setting them (as
-      documented in 'Writing R Extensions' SS1.2).
+      documented in 'Writing R Extensions' ?1.2).
 
       This has most effect where configure is used to compile parts of
       the package - most often by cmake or libtool which obfuscate the
@@ -810,7 +888,7 @@
 
     * time() now (also) uses the ts.eps = getOption("ts.eps") argument
       and thus by default rounds values very close to the start (or
-      end) of a year.  Based on a proposal by Andre"i V. Kostyrka on
+      end) of a year.  Based on a proposal by Andre? V. Kostyrka on
       R-help.
 
     * Printing of a factanal() result with just one factor and sort =
@@ -865,7 +943,7 @@
       now, fixing another inadvertent bug.
 
     * predict.lm(<model with offset>) now finds the offset in the
-      correct environment, thanks to Andr'e Gillibert's report and patch
+      correct environment, thanks to Andr? Gillibert's report and patch
       in PR#18456.
 
     * getInitial(<formula>) now finds the selfStart model in the
@@ -1077,7 +1155,7 @@
       intended effect.
 
     * as.POSIXlt(x) now also works with very large dates x, fixing
-      PR#18401 reported by Hannes M"uhleisen.
+      PR#18401 reported by Hannes M?hleisen.
 
     * Files can now be extracted even from very large zip archives
       (PR#18390, thanks to Martin Jakt).
@@ -1601,7 +1679,7 @@
     * USE_FC_LEN_T will become the default: this uses the correct
       prototypes for Fortran BLAS/LAPACK routines called from C/C++,
       and requires adjustment of most such calls - see 'Writing R
-      Extensions' SS6.6.1.  (This has been supported since R 3.6.2.)
+      Extensions' ?6.6.1.  (This has been supported since R 3.6.2.)
 
     * Package installation speed for packages installed with
       keep.source has been improved. This resolve the issue reported by
@@ -1626,7 +1704,7 @@
       declarations in C into a compilation error.
 
     * R CMD check --as-cran makes use of the environment variable
-      AUTORECONF.  See the "R Internals" manual SS8 for further details.
+      AUTORECONF.  See the "R Internals" manual ?8 for further details.
 
     * R CMD check --use-valgrind also uses valgrind when re-building
       vignettes as some non-Sweave vignettes unhelpfully comment out
@@ -1665,7 +1743,7 @@
       moved from the installed header Rinternals.h to the internal
       header Defn.h. Packages that only use entry points and
       definitions documented to be part of the API as specified in
-      'Writing R Extensions' SS6 should not be affected.
+      'Writing R Extensions' ?6 should not be affected.
 
     * The macro USE_RINTERNALS no longer has any effect when compiling
       package code.  Packages which also use R_NO_REMAP will need to
@@ -1674,9 +1752,8 @@
 
     * The deprecated legacy S-compatibility macros PROBLEM, MESSAGE,
       ERROR, WARN, WARNING, RECOVER, ... are no longer defined in
-      R_exts/RS.h (included by R.h).  Replace these by calls to
-      Rf_error and Rf_warning (defined in header R_ext/Error.h included
-      by R.h).
+      R_ext/RS.h (included by R.h).  Replace these by calls to Rf_error
+      and Rf_warning (defined in header R_ext/Error.h included by R.h).
 
       Header R_ext/RS.h no longer includes R_ext/Error.h.
 
@@ -1695,7 +1772,7 @@
       introduced in R 3.4.0 and are available even when
       STRICT_R_HEADERS is defined.
 
-    * rmultinom has been documented in 'Writing R Extensions' SS6 so is
+    * rmultinom has been documented in 'Writing R Extensions' ?6 so is
       now part of the R API.
 
     * Similarly, Rtanpi, called from R level tanpi() is now part of the
@@ -2009,7 +2086,7 @@
       patch by Jeroen Ooms in PR#18152.)
 
     * Setting the RNG to "Marsaglia-Multicarry" e.g., by RNGkind(), now
-      warns in more places, thanks to Andr'e Gillibert's report and
+      warns in more places, thanks to Andr? Gillibert's report and
       patch in PR#18168.
 
     * gray(numeric(), alpha=1/2) no longer segfaults, fixing PR#18183,
@@ -2291,7 +2368,7 @@
       and Gabe Becker's PR#18016.)
 
     * Lithuanian translations are now available.  (Thanks to Rimantas
-      Zakauskas.)
+      ?akauskas.)
 
     * names() now works for DOTSXP objects.  On the other hand, in
       R-lang, the R language manual, we now warn against relying on the
@@ -2499,7 +2576,7 @@
     * R CMD INSTALL and R CMD SHLIB make use of their flag --use-LTO
       when the LTO_OPT make macro is set in file etc/${R_ARCH}/Makeconf
       or in a personal/site Makevars file.  (For details see 'Writing R
-      Extensions' SS4.5.)
+      Extensions' ?4.5.)
 
       This provides a valuable check on code consistency.  It does work
       with GCC 8.3 as in Rtools40, but that does not detect everything
@@ -2535,7 +2612,7 @@
       LazyDataCompression is not specified without LazyData and has a
       documented value.  For packages with large LazyData databases
       without specifying LazyDataCompression, there is a reference to
-      the code given in 'Writing R Extensions' SS1.1.6 to test the
+      the code given in 'Writing R Extensions' ?1.1.6 to test the
       choice of compression (as in all the CRAN packages tested a
       non-default method was preferred).
 
@@ -3223,7 +3300,7 @@
     * sequence() is now an S3 generic with an internally implemented
       default method, and gains arguments to generate more complex
       sequences.  Based on code from the S4Vectors Bioconductor package
-      and the advice of Herv'e Pag`es.
+      and the advice of Herv? Pag?s.
 
     * print()'s default method and many other methods (by calling the
       default eventually and passing ...) now make use of a new
@@ -3583,7 +3660,7 @@
     * as.difftime() gets new optional tz = "UTC" argument which should
       fix behaviour during daylight-savings-changeover days, fixing
       PR#16764, thanks to proposals and analysis by Johannes Ranke and
-      Kirill M"uller.
+      Kirill M?ller.
 
     * round() does a better job of rounding _"to nearest"_ by
       _measuring_ and _"to even"_; thanks to a careful algorithm
@@ -3653,7 +3730,7 @@
       socket connection, allowing non-blocking read operations.
 
     * anova.glm() and anova.glmlist() computed incorrect score (Rao)
-      tests in no-intercept cases. (Andr'e Gillibert, PR#17735)
+      tests in no-intercept cases. (Andr? Gillibert, PR#17735)
 
     * summaryRprof() now should work correctly for the Rprof(*,
       memory.profiling=TRUE) case with small chunk size (and "tseries"
@@ -3669,7 +3746,7 @@
       compatibility for 16 years), fixing PR#17730.
 
     * x[[Inf]] (returning NULL) no longer leads to undefined behavior,
-      thanks to a report by Kirill M"uller in PR#17756.  Further,
+      thanks to a report by Kirill M?ller in PR#17756.  Further,
       x[[-Inf]] and x[[-n]] now give more helpful error messages.
 
     * Gamma() family sometimes had trouble storing link name PR#15891
diff -ru -P -x .mirror -x ls_lR -x Old R-release-orig/doc/NEWS.Rd R-patched/doc/NEWS.Rd
--- R-release-orig/doc/NEWS.Rd	2023-10-24 00:02:01.000000000 +0200
+++ R-patched/doc/NEWS.Rd	2024-01-23 17:45:06.940735789 +0100
@@ -5,6 +5,96 @@
 \title{R News}
 \encoding{UTF-8}
 
+\section{\Rlogo CHANGES IN R 4.3.2 patched}{
+
+  \subsection{NEW FEATURES}{
+    \itemize{
+      \item \code{iconv()} now fixes up variant encoding names such as
+      \code{"utf8"} case-insensitively.
+    }
+  }
+
+  \subsection{DEPRECATED AND DEFUNCT}{
+    \itemize{
+      \item The legacy \code{encoding = "MacRoman"} is deprecated in
+      \code{pdf()} and \code{postscript()}: support was incomplete in
+      earlier versions of \R.
+    }
+  }
+
+  \subsection{BUG FIXES}{
+    \itemize{
+      \item Arguments are now properly forwarded to methods on S4 generics
+      with \dots{} in the middle of their formal arguments. This was
+      broken for the case when a method introduced an argument but did
+      not include \dots{} in its own formals. Thanks to Hervé Pagès for
+      the report \PR{18538}.
+
+      \item Some invalid \code{file} arguments to \code{pictex()},
+      \code{postscript()} and \code{xfig()} opened a file called
+      \samp{NA} rather than throw an error.  These included
+      \code{postscript(NULL)} (which some people expected to work like
+      \code{pdf(NULL)}).
+
+      \item Passing \code{filename = NA} to \code{svg()}, \code{cairo_pdf()},
+      \code{cairo_ps()} or the Cairo-based bitmap devices opened a file
+      called \samp{NA}: it now throws an error.
+
+      \item \code{quartz(file = NA)} opened a file called \samp{NA}, including
+      when used as a Quartz-based bitmap device.  It now gives an error.
+
+      \item \code{rank(<long vector>)} now works, fixing \PR{18617}, thanks to
+      Ilia Kats.
+
+      \item \code{seq.int()} did not adequately check its
+      \code{length.out} argument.
+
+      \item \code{match(<POSIXct>, .)} is correct again for differing time
+      zones, ditto for \code{"POSIXlt"}, fixing \PR{18618} reported by
+      Bastian Klein.
+
+      \item \code{drop.terms(*, dropx = <0-length>)} now works, fixing
+      \PR{18563} as proposed by Mikael Jagan.
+
+      \item \code{drop.terms(*)} keeps \code{ + offset(.)} terms when it should,
+      \PR{18565}, and \code{drop.terms()} no longer makes up a response,
+      \PR{18566}, fixing both bugs thanks to Mikael Jagan.
+
+      \item \code{getS3method("t", "test")} no longer finds the
+      \code{t.test()} function, fixing \PR{18627}.
+
+      \item \code{pdf()} and \code{postscript()} support for the documented
+      Adobe encodings \code{"Greek"} and \code{"Cyrilllic"} was missing
+      (although the corresponding Windows' codepages could be used).
+
+      \item Computations of glyph metric information for \code{pdf()}
+      and \code{postscript()} did not take into account that
+      transliteration could replace one character by two or more (only
+      seen on macOS 14) and typically warned that the information was
+      not known.
+
+      \item \code{rank(x)} no longer overflows during integer addition, when
+      computing rank average for largish but not-yet long vector \code{x},
+      fixing \PR{18630}, thanks to Ilia Kats.
+
+      \item \code{list.files()} on Windows now returns also files with names
+      longer that 260 bytes (the Windows limit is 260 characters).
+      Previously, some file names particularly with \sQuote{East Asian}
+      characters were omitted.
+
+      \item \code{cov2cor(<0 x 0>)} now works, fixing \PR{18423} thanks to
+      Mikael Jagan and Elin Warning.
+
+      \item \code{cov2cor(<negative diagonal>)} and similar now give one
+      warning instead of two, with better wording, fixing \PR{18424} thanks
+      to Mikael Jagan.
+
+      \item \pkg{tools}\code{:: startDynamicHelp()} now ensures \code{port}
+      is in proper range, fixing \PR{18645}.
+    }
+  }
+}
+
 \section{\Rlogo CHANGES IN R 4.3.2}{
   \subsection{NEW FEATURES}{
     \itemize{
@@ -139,7 +229,7 @@
       diagnosed by Stephen Wade.
 
       \item The C prototypes for LAPACK calls \code{dspgv} and \code{dtptrs}
-      in \file{R_exts/Lapack.h} had one too many and one too few
+      in \file{R_ext/Lapack.h} had one too many and one too few
       character length arguments --- but this has not caused any known
       issues. To get the corrected prototypes, include
       \preformatted{
@@ -147,7 +237,7 @@
 	#ifdef PR18534fixed
 	# define usePR18534fix 1
         #endif
-	#include <R_exts/Lapack.h>
+	#include <R_ext/Lapack.h>
       }
       in your C/C++ code (\PR{18534}).
     }
@@ -1865,7 +1955,7 @@
       \item The deprecated legacy S-compatibility macros \code{PROBLEM},
       \code{MESSAGE}, \code{ERROR}, \code{WARN}, \code{WARNING},
       \code{RECOVER}, \dots{} are no longer defined in
-      \file{R_exts/RS.h} (included by \file{R.h}).  Replace these by
+      \file{R_ext/RS.h} (included by \file{R.h}).  Replace these by
       calls to \code{Rf_error} and \code{Rf_warning} (defined in header
       \file{R_ext/Error.h} included by \file{R.h}).
 
Binary files R-release-orig/doc/NEWS.pdf and R-patched/doc/NEWS.pdf differ
diff -ru -P -x .mirror -x ls_lR -x Old R-release-orig/doc/RESOURCES R-patched/doc/RESOURCES
--- R-release-orig/doc/RESOURCES	2023-10-31 09:02:29.000000000 +0100
+++ R-patched/doc/RESOURCES	2024-02-11 01:32:14.601172687 +0100
@@ -9,9 +9,9 @@
 
      <https://CRAN.R-project.org/doc/FAQ/R-FAQ.html>
 
-A text version is in file 'FAQ' in this directory, and an HTML version is
-available as file 'doc/html/faq.html' and via the on-line help (on the index
-page given by 'help.start()').
+A text version is in file ‘FAQ’ in this directory, and an HTML version is
+available as file ‘doc/html/faq.html’ and via the on-line help (on the index
+page given by ‘help.start()’).
 
 2 Mailing lists
 ***************
diff -ru -P -x .mirror -x ls_lR -x Old R-release-orig/doc/html/NEWS.html R-patched/doc/html/NEWS.html
--- R-release-orig/doc/html/NEWS.html	2023-10-31 09:05:19.000000000 +0100
+++ R-patched/doc/html/NEWS.html	2024-02-11 01:35:37.486555765 +0100
@@ -18,6 +18,128 @@
 
 <h2 id='NEWS'>R News</h2>
 
+<h3><img src="../help/figures/../../html/Rlogo.svg" class="toplogo" alt="[R logo]" /> CHANGES IN R 4.3.2 patched</h3>
+
+
+
+<h4>NEW FEATURES</h4>
+
+
+<ul>
+<li> <p><code>iconv()</code> now fixes up variant encoding names such as
+<code>"utf8"</code> case-insensitively.
+</p>
+</li></ul>
+
+
+
+
+<h4>DEPRECATED AND DEFUNCT</h4>
+
+
+<ul>
+<li><p> The legacy <code>encoding = "MacRoman"</code> is deprecated in
+<code>pdf()</code> and <code>postscript()</code>: support was incomplete in
+earlier versions of <span class="rlang"><b>R</b></span>.
+</p>
+</li></ul>
+
+
+
+
+<h4>BUG FIXES</h4>
+
+
+<ul>
+<li><p> Arguments are now properly forwarded to methods on S4 generics
+with ... in the middle of their formal arguments. This was
+broken for the case when a method introduced an argument but did
+not include ... in its own formals. Thanks to Hervé Pagès for
+the report <a href="https://bugs.R-project.org/show_bug.cgi?id=18538">PR#18538</a>.
+</p>
+</li>
+<li><p> Some invalid <code>file</code> arguments to <code>pictex()</code>,
+<code>postscript()</code> and <code>xfig()</code> opened a file called
+&lsquo;<span class="samp">&#8288;NA&#8288;</span>&rsquo; rather than throw an error.  These included
+<code>postscript(NULL)</code> (which some people expected to work like
+<code>pdf(NULL)</code>).
+</p>
+</li>
+<li><p> Passing <code>filename = NA</code> to <code>svg()</code>, <code>cairo_pdf()</code>,
+<code>cairo_ps()</code> or the Cairo-based bitmap devices opened a file
+called &lsquo;<span class="samp">&#8288;NA&#8288;</span>&rsquo;: it now throws an error.
+</p>
+</li>
+<li> <p><code>quartz(file = NA)</code> opened a file called &lsquo;<span class="samp">&#8288;NA&#8288;</span>&rsquo;, including
+when used as a Quartz-based bitmap device.  It now gives an error.
+</p>
+</li>
+<li> <p><code>rank(&lt;long vector&gt;)</code> now works, fixing <a href="https://bugs.R-project.org/show_bug.cgi?id=18617">PR#18617</a>, thanks to
+Ilia Kats.
+</p>
+</li>
+<li> <p><code>seq.int()</code> did not adequately check its
+<code>length.out</code> argument.
+</p>
+</li>
+<li> <p><code>match(&lt;POSIXct&gt;, .)</code> is correct again for differing time
+zones, ditto for <code>"POSIXlt"</code>, fixing <a href="https://bugs.R-project.org/show_bug.cgi?id=18618">PR#18618</a> reported by
+Bastian Klein.
+</p>
+</li>
+<li> <p><code>drop.terms(*, dropx = &lt;0-length&gt;)</code> now works, fixing
+<a href="https://bugs.R-project.org/show_bug.cgi?id=18563">PR#18563</a> as proposed by Mikael Jagan.
+</p>
+</li>
+<li> <p><code>drop.terms(*)</code> keeps <code> + offset(.)</code> terms when it should,
+<a href="https://bugs.R-project.org/show_bug.cgi?id=18565">PR#18565</a>, and <code>drop.terms()</code> no longer makes up a response,
+<a href="https://bugs.R-project.org/show_bug.cgi?id=18566">PR#18566</a>, fixing both bugs thanks to Mikael Jagan.
+</p>
+</li>
+<li> <p><code>getS3method("t", "test")</code> no longer finds the
+<code>t.test()</code> function, fixing <a href="https://bugs.R-project.org/show_bug.cgi?id=18627">PR#18627</a>.
+</p>
+</li>
+<li> <p><code>pdf()</code> and <code>postscript()</code> support for the documented
+Adobe encodings <code>"Greek"</code> and <code>"Cyrilllic"</code> was missing
+(although the corresponding Windows' codepages could be used).
+</p>
+</li>
+<li><p> Computations of glyph metric information for <code>pdf()</code>
+and <code>postscript()</code> did not take into account that
+transliteration could replace one character by two or more (only
+seen on macOS 14) and typically warned that the information was
+not known.
+</p>
+</li>
+<li> <p><code>rank(x)</code> no longer overflows during integer addition, when
+computing rank average for largish but not-yet long vector <code>x</code>,
+fixing <a href="https://bugs.R-project.org/show_bug.cgi?id=18630">PR#18630</a>, thanks to Ilia Kats.
+</p>
+</li>
+<li> <p><code>list.files()</code> on Windows now returns also files with names
+longer that 260 bytes (the Windows limit is 260 characters).
+Previously, some file names particularly with &lsquo;East Asian&rsquo;
+characters were omitted.
+</p>
+</li>
+<li> <p><code>cov2cor(&lt;0 x 0&gt;)</code> now works, fixing <a href="https://bugs.R-project.org/show_bug.cgi?id=18423">PR#18423</a> thanks to
+Mikael Jagan and Elin Warning.
+</p>
+</li>
+<li> <p><code>cov2cor(&lt;negative diagonal&gt;)</code> and similar now give one
+warning instead of two, with better wording, fixing <a href="https://bugs.R-project.org/show_bug.cgi?id=18424">PR#18424</a> thanks
+to Mikael Jagan.
+</p>
+</li>
+<li> <p><span class="pkg">tools</span><code>:: startDynamicHelp()</code> now ensures <code>port</code>
+is in proper range, fixing <a href="https://bugs.R-project.org/show_bug.cgi?id=18645">PR#18645</a>.
+</p>
+</li></ul>
+
+
+
+
 <h3><img src="../help/figures/../../html/Rlogo.svg" class="toplogo" alt="[R logo]" /> CHANGES IN R 4.3.2</h3>
 
 
@@ -201,7 +323,7 @@
 </p>
 </li>
 <li><p> The C prototypes for LAPACK calls <code>dspgv</code> and <code>dtptrs</code>
-in &lsquo;<span class="file">R_exts/Lapack.h</span>&rsquo; had one too many and one too few
+in &lsquo;<span class="file">R_ext/Lapack.h</span>&rsquo; had one too many and one too few
 character length arguments &mdash; but this has not caused any known
 issues. To get the corrected prototypes, include
 </p>
@@ -210,7 +332,7 @@
 	#ifdef PR18534fixed
 	# define usePR18534fix 1
         #endif
-	#include &lt;R_exts/Lapack.h&gt;
+	#include &lt;R_ext/Lapack.h&gt;
       </pre>
 <p>in your C/C++ code (<a href="https://bugs.R-project.org/show_bug.cgi?id=18534">PR#18534</a>).
 </p>
@@ -2400,7 +2522,7 @@
 <li><p> The deprecated legacy S-compatibility macros <code>PROBLEM</code>,
 <code>MESSAGE</code>, <code>ERROR</code>, <code>WARN</code>, <code>WARNING</code>,
 <code>RECOVER</code>, ... are no longer defined in
-&lsquo;<span class="file">R_exts/RS.h</span>&rsquo; (included by &lsquo;<span class="file">R.h</span>&rsquo;).  Replace these by
+&lsquo;<span class="file">R_ext/RS.h</span>&rsquo; (included by &lsquo;<span class="file">R.h</span>&rsquo;).  Replace these by
 calls to <code>Rf_error</code> and <code>Rf_warning</code> (defined in header
 &lsquo;<span class="file">R_ext/Error.h</span>&rsquo; included by &lsquo;<span class="file">R.h</span>&rsquo;).
 </p>
diff -ru -P -x .mirror -x ls_lR -x Old R-release-orig/doc/html/R-admin.html R-patched/doc/html/R-admin.html
--- R-release-orig/doc/html/R-admin.html	2023-10-31 09:07:28.000000000 +0100
+++ R-patched/doc/html/R-admin.html	2024-02-11 01:43:28.021950012 +0100
@@ -1,11 +1,11 @@
-<!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN" "http://www.w3.org/TR/html4/loose.dtd">
+<!DOCTYPE html>
 <html>
-
+
 <head>
 <meta http-equiv="Content-Type" content="text/html; charset=utf-8">
-
+
 <head>
 <meta http-equiv="Content-Type" content="text/html; charset=utf-8">
 <title>R Resources</title>
@@ -18,21 +18,6 @@
 <link href="dir.html#Top" rel="prev" title="(dir)">
 <style type="text/css">
  max used: 92322 Mb
 })
 
@@ -360,6 +360,7 @@
 Ln # gave  Error: long vectors not supported yet: ...
 LL # gave  Error: long vect...
 options(op)
+rm(Ln, L)
 
 ## PR#17977 --- x[<fractional>] behavior should fulfill x[i] === x[as.integer(i)]
 ## large (no overflow in index computations!) -- needs 2 GB
@@ -368,8 +369,8 @@
 print(eps, digits=3)
 LL[cbind(2, ca.half)]   # should be of length 0, too: ca.half ~= 0.5
 LL[cbind(1, 1+ca.half)] # should be constantly == raw(1L) '01'
-LL[cbind(2+ca.half, 1)] # all 02
-LL[cbind(-ca.half, 1)] # raw(0) --- correct
+LL[cbind(2+ca.half, 1)] # all 02 -- failed in R <= 4.1.x
+LL[cbind(-ca.half, 1)]  # raw(0) --  "      "    "
 stopifnot(exprs = {
     length(LL[cbind(2, ca.half)]) == 0
     LL[cbind(1, 1+ca.half)] == as.raw(1L)
@@ -377,5 +378,22 @@
     length(LL[cbind( -ca.half, 1)]) == 0
 })
 
+
+x <- -1:2^31 # (immediate: ALTREP)
+system.time( r <- rank(x) )# Error about invalid length() -- PR#18617, in R <= 4.3.2
+## seen 260 sec (!)
+head(r)
+stopifnot(r[1:6] == 1:6)
+rm(r,x)
+
+## rank(<largish) -- PR#18630
+vals <- 1:1475000000 # (immedate, thanks to ALTREP)
+system.time( ranks <- rank(vals) ) # ~ 130 sec
+head(ranks, 11)
+stopifnot(ranks[1:11] == 1:11, min(ranks) == 1)
+## min(ranks) was -1073741824, in R <= 4.3.2
+
+
+
 gc() # NB the "max used"
-proc.time() # total  [ ~ 40 minutes in full case, 2019-04-12]
+proc.time() # total  [ ~ 50 minutes in full case, 2024-01; was 40' in 2019-04-12]
diff -ru -P -x .mirror -x ls_lR -x Old R-release-orig/tests/reg-tests-1e.R R-patched/tests/reg-tests-1e.R
--- R-release-orig/tests/reg-tests-1e.R	2023-06-07 00:15:01.000000000 +0200
+++ R-patched/tests/reg-tests-1e.R	2024-01-23 17:45:07.725691614 +0100
@@ -382,7 +382,9 @@
 names(cls) <- cls
 be <- baseenv()
 asF  <- lapply(cls, \(cl) be[[paste0("as.",cl)]] %||% be[[cl]])
-obs  <- lapply(cls, \(cl) asF[[cl]](switch(cl, "difftime" = "2:1:0", "noquote" = letters, 1:2)))
+## objects of the respective class:
+obs  <- lapply(cls, \(cl) asF[[cl]](switch(cl, "difftime" = "2:1:0", "noquote" = letters,
+                                           "numeric_version" = as.character(1:2), 1:2)))
 asDF <- lapply(cls, \(cl) getVaW(be[[paste0("as.data.frame.", cl)]](obs[[cl]])))
 r <- local({ g <- as.data.frame.logical; f <- function(L=TRUE) g(L)
     getVaW(f()) })
@@ -561,6 +563,21 @@
 ## was wrong in R 4.3.0 (and R-devel for a while)
 
 
+## Methods of a non-generic function
+foo <- function(x) { bar(x) }
+(m <- methods(foo))
+stopifnot(inherits(m, "MethodsFunction"), length(m) == 0L)
+## .S3methods() failed in R-devel for a few days after r84400.
+
+
+## getS3method() error
+myFUN <- function(x) UseMethod("myFUN")
+(msg <- tryCmsg(getS3method("myFUN", "numeric")))
+if(englishMsgs)
+    stopifnot(grepl("S3 method 'myFUN.numeric' not found", msg))
+## failed with "wrong" message after r84400
+
+
 ## head(.,n) / tail(.,n) error reporting - PR#18362
 try(head(letters, 1:2)) # had "Error in checkHT(..)"); now ".. in head.default(..)"
 try(tail(letters, NA))
@@ -630,6 +647,206 @@
 ## coef.foo  part  always worked
 
 
+## contrib.url() should "recycle0"
+stopifnot(identical(contrib.url(character()), character()))
+## R <= 4.3.1 returned "/src/contrib" or similar
+
+
+## `substr<-` overrun in case of UTF-8 --- private bug report by 'Architect 95'
+s0 <- "123456"; nchar(s0) #  6
+substr(s0, 6, 7) <- "cc"
+s0 ; nchar(s0) # {"12345c", 6}: all fine: no overrun, silent truncation
+(s1 <- intToUtf8(c(23383, 97, 97, 97, 97, 97))); nchar(s1)  # "字aaaaa" , 6
+substr(s1, 6, 7) <- "cc"
+# Now s1 should be "字aaaac", but  actually did overrunn nchar(s1);
+s1; nchar(s1) ## was "字aaaacc", nchar  = 7
+(s2 <- intToUtf8(c(23383, 98, 98))); nchar(s2)  # "字bb" 3
+substr(s2, 4, 5) <- "dd" # should silently truncate as with s0:
+## --> s2 should be "字bb", but was "字bbdddd\x97" (4.1.3) or "字bbdd字" (4.3.1)
+s2; nchar(s2) ## was either 6 or  "Error ... : invalid multibyte string, element 1"
+#-------------
+## Example where a partial UTF-8 character is included in the second string
+## 3) all fine
+(s3 <- intToUtf8(c(23383, 97, 97, 97, 97, 97))); nchar(s3)  # "字aaaaa" 6
+substr(s3, 6, 6) <- print(intToUtf8(23383))  # "字"
+s3 ; nchar(s3) # everything as expected:  ("字aaaa字", 6)
+## 4) not good
+(s4 <- intToUtf8(c(23383, 98, 98, 98, 98))); nchar(s4) # "字bbbb" 5
+substr(s4, 5, 7) <- "ddd"
+# Now s4 should be "字bbbd", but was "字bbbddd\x97", (\x97 = last byte of "字" in UTF-8)
+s4; nchar(s4)## gave "字bbbddd\x97" and "Error ...: invalid multibyte string, element 1"
+stopifnot(exprs = {
+    identical(s0, "12345c") # always ok
+    identical(utf8ToInt(s1), c(23383L, rep(97L, 4), 99L))           ; nchar(s1) == 6
+    identical(utf8ToInt(s2), c(23383L, 98L, 98L))                   ; nchar(s2) == 3
+    identical(utf8ToInt(s3), c(23383L, 97L, 97L, 97L, 97L, 23383L)) ; nchar(s3) == 6
+    identical(utf8ToInt(s4), c(23383L, 98L, 98L, 98L, 100L))        ; nchar(s4) == 5
+    Encoding(c(s1,s2,s3,s4)) == rep("UTF-8", 4)
+})
+## did partly overrun to invalid strings, nchar(.) giving error in R <= 4.3.1
+
+
+## PR#18557 readChar() with large 'nchars'
+ch <- "hello\n"; tf <- tempfile(); writeChar(ch, tf)
+tools::assertWarning((c2 <- readChar(tf, 4e8)))
+stopifnot(identical(c2, "hello\n"))
+## had failed w/   cannot allocate memory block of size 16777216 Tb
+
+
+## Deprecation of *direct* calls to as.data.frame.<someVector>
+dpi <- as.data.frame(pi)
+d1 <- data.frame(dtime = as.POSIXlt("2023-07-06 11:11")) # gave F.P. warning
+r <- lapply(list(1L, T=T, pi=pi), as.data.frame)
+stopifnot(is.list(r), is.data.frame(d1), inherits(d1[,1], "POSIXt"), is.data.frame(r$pi), r$pi == pi)
+stopifnot(local({adf <- as.data.frame; identical(adf(1L),(as.data.frame)(1L))}))
+## Gave 1 + 3 + 2  F.P. deprecation warnings in 4.3.0 <= R <= 4.3.1
+str(d2 <- mapply(as.data.frame, x=1:3, row.names=letters[1:3]))
+stopifnot(is.list(d2), identical(unlist(unname(d2)), 1:3))
+## gave Error .. sys.call(-1L)[[1L]] .. comparison (!=) is possible only ..
+
+
+## qqplot(x,y, *) confidence bands for unequal sized x,y, PR#18570:
+x <- (7:1)/8; y <- (1:63)/64
+r <- qqplot(x,y, plot.it=FALSE, conf.level = 0.90)
+r2<- qqplot(y,x, plot.it=FALSE, conf.level = 0.90)
+(d <- 64 * as.data.frame(r)[,3:4])
+stopifnot(identical(d, data.frame(lwr = c(NA, NA, NA, 6, 15, 24, 33),
+                                  upr = c(31, 40, 49, 58, NA, NA, NA))),
+          identical(8 * as.data.frame(r2[3:4]),
+                    data.frame(lwr = c(NA,NA,NA, 1:4 +0), upr = c(4:7 +0, NA,NA,NA))))
+## lower and upper confidence bands were nonsensical in R <= 4.3.1
+
+
+## isoreg() seg.faulted with Inf - PR#18603 - in R <= 4.3.1
+assertErrV(isoreg(Inf))
+assertErrV(isoreg(c(0,Inf)))
+assertErrV(isoreg(rep(1e307, 20))) # no Inf in 'y'
+## ==> Asserted error: non-finite sum(y) == inf is not allowed
+
+
+## Conversion of LaTeX accents: \~{n} etc vs. \~{}, accented I and i
+stopifnot(identical(
+    print(tools::parseLatex("El\\~{}Ni\\~{n}o") |>
+          tools::latexToUtf8() |>
+          tools::deparseLatex(dropBraces = TRUE)),
+    "El~Ni\u00F1o")) # "El~Niño"
+## gave "El~Ni~no" in R 4.3.{0,1} (\~ treated as 0-arg macro)
+stopifnot(tools:::cleanupLatex(r"(\`{I}\'{I}\^{I}\"{I})")
+          == "\u00cc\u00cd\u00ce\u00cf")
+## was wrongly converted as "ËÌÍÏ" in R <= 4.3.1
+stopifnot(tools:::cleanupLatex(r"(\`{i}\'{i}\^{i}\"{i})")
+          == "\u00ec\u00ed\u00ee\u00ef")
+## codes with i instead of \i were unknown thus not converted in R <= 4.3.1
+
+
+## PR#18618: match()  incorrect  with POSIXct || POSIXlt || fractional sec
+(dCT <- seq(as.POSIXct("2010-10-31", tz = "Europe/Berlin"), by = "hour", length = 5))
+(dd <- diff(dCT))
+chd <- as.character(dCT)
+vdt <- as.vector   (dCT)
+dLT <- as.POSIXlt  (dCT)
+dat <- as.Date     (dCT)
+dL2 <- dLT[c(1:5,5)]; dL2[6]$sec <- 1/4
+dL. <- dL2          ; dL.[6]$sec <- 1e-9
+stopifnot(exprs = {
+    inherits(dCT, "POSIXct")
+    inherits(dLT, "POSIXlt")
+    !duplicated(dCT)
+    dd == 1
+    units(dd) == "hours"
+    diff(as.integer(dCT)) == 3600L # seconds
+    identical(match(chd, chd), c(1:3, 3L, 5L))
+    identical(match(vdt, vdt), seq_along(vdt))
+    identical(match(dat, dat), c(1L,1L, 3L,3L,3L)) # always ok
+    identical(match(dCT, dCT), seq_along(dCT)) # wrong in 4.3.{0,1,2}
+    identical(match(dLT, dLT), seq_along(dLT)) #  "    "   "
+    identical(match(dL2, dL2), seq_along(dL2)) #  "    "   "
+    identical(match(dL., dL.), seq_along(dL.)) #  "    "  now ok, as indeed,
+  ! identical(dL.[5], dL.[6]) # NB: `==`, diff(), ... all lose precision, from as.POSIXct():
+    inherits(dC. <- as.POSIXct(dL.), "POSIXct")
+    identical(match(dC., dC.), c(1:5, 5L))
+    identical(dC.[5], dC.[6])
+    dC.[5] == dC.[6]
+} )
+## failed (partly) in R versions  4.3.0 -- 4.3.2
+
+
+## PR#18598: *wrong* error message
+writeLines(eMsg <- tryCmsg(
+    diff(1:6, differences = integer(0L))
+))
+if(englishMsgs) stopifnot(grepl("must be integers >= 1", eMsg))
+## errored with "missing value where TRUE/FALSE needed" in R <= 4.3.2
+
+
+## PR#18563: drop.terms(*, dropx = <0-length vector>)
+tt <- terms(y ~ a+b)
+stopifnot(identical(tt, drop.terms(tt, dropx = 0[0], keep.response=TRUE)))
+## errored in R <= 4.3.2
+
+
+## PR#18627 - getS3method() should match method dispatch {and isS3method()}
+stopifnot(exprs = {
+            ! isS3method("t", "test")
+    is.null( getS3method("t", "test", optional=TRUE) )
+    identical(dim(t(structure(matrix(, 3, 2), class = "test"))), # t.test() is *not* called:
+              2:3)
+})
+## getS3method(..) did return the t.test function, in R <= 4.3.2
+
+
+## PR#18564,5,6:  drop.terms(*)
+tt <- terms(y ~ a+b)
+stopifnot(formula(drop.terms(tt))                     == {   ~ a+b }) # was  y ~ a + b
+stopifnot(formula(drop.terms(tt, keep.response=TRUE)) == { y ~ a+b }) # (unchanged)
+## did not drop y (with default keep.response=FALSE) in R <= 4.3.2
+##
+## PR#18565: offset() in formula
+tto <- terms(y ~ a + b + offset(h))
+(ttF <- drop.terms(tto, 1L, keep.response = FALSE))
+(ttT <- drop.terms(tto, 1L, keep.response = TRUE ))
+(tt.2 <- tto[2L])
+stopifnot(exprs = {
+    formula(ttF) ==     ~ b + offset(h)
+    formula(ttT) == { y ~ b + offset(h) }
+    formula(tt.2)== { y ~ b + offset(h) }
+    identical(attr(ttF, "offset"), 2L)
+    identical(attr(ttT, "offset"), 3L)
+    identical(attr(tt.2,"offset"), 3L)
+}) ## all dropped 'offset' in R <= 4.3.2
+##
+## PR#18566:
+t2 <- terms(~ a + b)
+str(dt2 <- drop.terms(t2, 1, keep.response = TRUE))
+stopifnot( drop.terms(t2, 1) == dt2, dt2 == ~ b)
+## gave a+b ~ b in R <= 4.3.2
+
+
+## cov2cor(<0x0>) PR#18423
+m00 <- matrix(0,0,0)
+stopifnot(identical(cov2cor(m00), m00))
+## gave error in R <= 4.3.2
+
+
+## cov2cor(.) warning(s) with negative/NA diag(.) - PR#18424
+(D_1 <- diag(-1, 3L))
+op <- options(warn=1)
+m <- capture.output(r <- cov2cor(D_1), type = "message")
+matrix(rep_len(c(1, rep(NaN,3)),3*3), 3) -> r0
+stopifnot(all.equal(r, r0, tol = 0, check.attributes = FALSE),# always ok
+          length(m) == 2, grepl("^ *diag.V. ", m[2]))
+options(op) # revert
+## cov2cor() gave 2 warnings on 3 lines, the 2nd one inaccurate in R <= 4.3.2
+
+
+## startDynamicHelp(): port out of range, PR#18645
+op <- options(help.ports = 123456L)
+assertErrV(tools::startDynamicHelp())
+assertErrV(help.start(browser = identity))
+options(op)
+## silently failed much later in R <= 4.3.2.
+
+
 
 ## keep at end
 rbind(last =  proc.time() - .pt,

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