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- Update to version 2.8.1:
  * Parameter estimation
    + stk_optim_octavesqp/stk_minimize_boxconstrained.m: Catch
      sqp errors and return the best point found so far.
  * Maintainer tools
    + stk_runtests.m: Optionnally, save the result to a mat-file.
    + stk_runtests_allmatlabs.m: Run the test suite on all
      available versions of Matlab.
    + admin/build_tools: Simplify HTML doc build

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- Update to version 2.8.0:
  * Required Octave version number has been raised to 4.0.1.
  * Test functions:
    + stk_testfun_hartman3.m, stk_testfun_hartman6.m: New test
      functions (“Hartman3” and “Hartman6”) from the Dixon & Szego
      (1978) benchmark.
    + stk_testfun_hartman4.m: New test function (“Hartman4”) based
      on Picheny et al (2013), with a different scaling.
    + Most test functions in examples/test_functions are now also
      available under the CC0 license (see each file).

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Update to version 2.7.0

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- Update to version 2.6.1:
  * Documentation
    + stk_factorialdesign: Provide missing help text. (ticket #91)
    + Fix HTML doc (INDEX structure was broken).
- Update to version 2.6.0:
  * Required Octave version
    + Required Octave version number has been raised to 3.8.
  * Parameter estimation
    + stk_param_init: The syntax with an additional do_estim_lnv parameter
      is now deprecated. Set model.lognoisevariance to NaN if you want an
      initial estimate for the variance of the noise.
    + stk_param_init_lnv: Refuse noiseless models (error).
    + stk_model_gpposterior: Trigger parameter estimation when lognoisevariance
      is NaN. In the (experimental) case where lognoisevariance is a noise
      model object, parameter estimation is triggered as soon as at least one
      of the optimizable parameters of the model is NaN. (ticket #93)
    + stk_param_relik: Return [] instead of NaN when the derivative with
      respect to lnv is requested for a noiseless model.
    + stk_param_relik: Detect duplicated observation points automatically
      and raise an error for noiseless models.
    + stk_param_getdefaultbounds: Estimation bounds for the regularity parameter
      of the Matérn covariance function are now customizable through the options
      nu_min_dimfun and nu_max_dimfun.
  * Covariance functions
    + Deprecated: stk_noisecov.
  * Models
    + stk_get_input_data, stk_get_output_data, stk_get_prior_model: New getters
      for model properties, that replace get_input_data, get_output_data and
      get_prior_model respectively (now deprecated).
    + stk_get_observation_variances: New getter, which returns the vector of
      variances associated to the observations that have been used to build a model.
    + stk_gaussiannoise_, stk_gaussiannoise_het0: New classes representing Gaussian
      noise models. Currently in experimental state, these two classes are merely a
      proof-of-concept. Other noise model classes can be defined by subclassing
      stk_gaussiannoise_. (ticket #38)
    + stk_example_misc05: Demonstrate the use of noise model objects to estimate
      the dispersion parameter in an heteroscedatic case.
    + stk_simulate_noise: New function to simulate noise sample replicates.
  * stk_dataframe and related classes
    + stk_dataframe: Accept char vectors (or strings) as colnames or rownames
      argument when there is only one column or one row (ticket #92)
    + @stk_dataframe/sort: Argument dim can now be skipped, as in the base sort function.
    + @stk_dataframe/unique: Overload base function.
  * Graphics
    + stk_plot1d: Do not create a legend systematically. (ticket #82)
    + stk_legend: New function to create a legend, using the graphical objects for
      which a non-empty DisplayName has been provided.
    + stk_plot_shadedci: Change gray levels and improve legend.
  * Miscellaneous
    + stk_options_set: Make it possible to set all options at once using an option
      structure. Add help text.
    + stk_runtests: Return test results in a structure.
    + stk_sampling_nesteddesign: Fix help text.

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- Update to version 2.5.0
  * Required Octave version number has been raised to 3.6.0.
  * Sequential design of experiments:
    - `stk_sampcrit_akg_eval`: New function.  Computes the
      Approximate Knowledge Gradient (AKG) sampling criterion.
    - `stk_example_doe05`: Example script that demonstrates the
      use of the AKG and EQI sampling criteria for noisy
      optimization.
    - New (experimental) classes to represent sampling criterion
      objects: `stk_sampcrit_ei`, `stk_sampcrit_akg`,
      `stk_sampcrit_eqi`.
    - `stk_sampcrit_ei_eval`: Remove deprecated calling forms.
  * Design of experiments:
    - `stk_factorialdesign`: Accept one-variable `stk_dataframe`
      objects as factors and preserve column names in this case.
    - `stk_sampling_nesteddesign`: New function to create nested
      designs.
    - `stk_sampling_nestedlhs`: New function to create nested LHS
      (NLHS).
    - `stk_sampling_sobol`: Fix help text.
  * Validation of models:
    - `stk_distrib_normal_crps`: New function to compare
      observations and predictive (Gaussian) density.
    - Calling `stk_predict_leaveoneout` with no output arguments
      now automatically creates two cross-validation diagnostics
      in two subplots: prediction VS observations (left panel) and
      normalized residuals (right panel).
    - `stk_predict_leaveoneout` uses now the virtual LOO formula.
  * `stk_dataframe` and related classes
    - `stk_hrect`: Preserve column names for `stk_dataframe`

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- Update to version 2.3.4
  * Bug fixes and minor changes

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- Update to version 2.3.2
  * Bug fixes and minor changes

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