Required Matlab version number has been raised to R2009b.
Required Octave version number has been raised to 4.0.0.
stk_predict.m now officially supports a shorter calling syntax:
[zp, ...] = skt_predict (model, x_prd)
that can be used either to compute predictions from any type of model (proper prior model structures, posterior model object, (experimental) noise model objects, etc.).
@stk_model_gpposterior/stk_predict.m: no longer exists. The base
stk_predict function now provides the recommended interface for
all possible types of models, and then dispatches to the (new)
internal function stk_predict_ to do the actual computations (but
do not rely on it directly, since this is an internal function).
get_input_data, get_output_data, get_prior_model: Removed
(these getters were already deprecated, cf. STK 2.6.0 release notes).stk_dataframe arrays now possess a sample_size property, which
can be read using the usual dot-indexing notation or through the
(slightly faster) getter stk_get_sample_size.
stk_model_gpposterior objects also have a sample_size property,
which corresponds to the sample size of the underlying data set and
can be read similarly.
stk_length: deprecated (use stk_get_sample_size instead).
@stk_model_gpposterior/stk_{set,get}_optimizable_parameters.m: Fix
a bug (erroneous property name).
@stk_sampcrit_akg/set.m: Remove replicated input points when the AKG
reference grid is construted using Scott's original method (i.e., taking
past observations points plus the candidate point).stk_example_kb07.m: Add a second figure where nu is fixed to 5/2
and rho varies.
stk_example_doe05.m: Make it possible to use the exact KG criterion
instead of Scott's approximation (previously, only the latter was
proposed).
stk_example_doe06.m: New example script, which illustrates a
simple sequential design strategy to estimate an excursion set
(failure region) and its volume (probability of failure).
stk_init.m: Make STK startup faster.
startup.m: Run stk_init automatically for in-place use.
stk_select_optimizer.m, stk_optim_hasfmincon.m: Removed
(had been deprecated since 2015, and were never part of the public API).
README.md: Explain how to initialize STK when using the Parallel
Computing Toolbox in Matlab, by means of the pctRunOnAll function.
Internal: source formatting, comments, etc.
stk_factorialdesign: Provide missing help text.
(ticket #91)
Fix HTML doc (INDEX structure was broken).
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.
stk_noisecov.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 classesstk_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.
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.
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.
stk_dominatedhv: Workaround for Octave 4.4 issue
(ticket #89)Documentation fixes.
stk_option_set: Return option struct only if nargout > 0.
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.
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.
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 classesstk_hrect: Preserve column names for stk_dataframe inputs.
@stk_dataframe/find: Overload base function to support calling find
with an stk_dataframe as first input argument.
@stk_dataframe/plotmatrix: Overload base function to enrich
plotmatrix graphics with variable names when possible.
Logical functions
Operations that normally return logical (lt, eq, and...) now
return logical values for stk_dataframe arguments.
New overloaded functions for stk_dataframe objects: isinf,
isnan, isfinite.
Testing array membership
@stk_dataframe/ismember: No longer assumes rows flag for
consistency with the base ismember function.
stk_factorialdesign/ismember: New function. Tests membership
for factorial designs much more efficiently than for plain arrays
or data frames.
stk_generate_samplepaths now returns a plain numerical array instead of
a data frame.
stk_plot_probdom2d: New function to represent the uncertainty about a
2D Pareto front. This function is currently considered experimental and
should not be expected to produce a reliable representation of the
uncertainty for difficult or high-dimensional optimization problems.
New test case: "truss3" (Koski, 1985; Das, 1997).
Many functions have been optimized for speed.
stk_plot1d: Handle the case where xt is not sorted.
Support old-style STK structures (with a .a field) has been removed.
stk_model_gpposterior objects in Octave 4.2
(ticket #73).stk_pmisclass: Handle properly the case where K22 is negative or
null.
stk_get_optimizable_parameters, stk_get_optimizable_parameters: Fix
syntax errors.
stk_param_estim: Issue a better error message when LNV0 (the starting
point for the estimation of the lognoisevariance parameter) is either
NaN of infinite (ticket #72).
stk_sampcrit_ei_eval: The function now has a new syntax. The other
syntaxes, introduced (accidentally) in STK 2.4.0, will remain supported
in 2.4.x, but are deprecated and will be removed in a future release.
Unlike the older stk_distrib_normal_ei function, stk_sampcrit_ei_eval
is written for a minimization problem, following the usual convention
in optimization software.
From now on, it is recommended to use stk_sampcrit_ei_eval instead of
stk_distrib_normal_ei.
stk_sampcrit_emmi_eval: Now accepts for the input argument ZI a set
of observations that contains dominated solutions (rows). Dominated rows
and duplicates are removed automatically, as in stk_sampcrit_ehvi_eval.
stk_pmisclass, stk_sampcrit_ei_eval, stk_sampcrit_ehvi_eval: Help
text has been added for all these functions.stk_param_estimThe choice of the optimization algorithm used in stk_param_estim is now
much more flexible, thanks to a new interface based on "optimizer object"
classes.
The following classes are currently available: @stk_optim_octavesqp,
@stk_optim_fmincon, @stk_optim_fminsearch.
stk_optim_octavesqp works both in Octave and in Matlab, with two
possible choices for the QP solver: qp (available in Octave only, this
is Octave's core qp function) and quadprog (available in Matlab from
the Optimization toolbox or from MOSEK; should be available in Octave's
optim package soon).
Automatic detection of available optimizers.
stk_minimize_boxconstrained (new function): Perform box-constrained
minimization of a function. This function is overloaded for each
optimizer object class that supports box-constrained optimization.
stk_minimize_unconstrained (new function): Perform unconstrained
minimization of a function. This function is overloaded for each
optimizer object class that supports unconstrained optimization.
It is now possible to specify default bounds for the estimation of the
parameters in a user-defined covariance function. See the documentation
of stk_param_getdefaultbounds for more information.
Experimental/undocumented feature: it is possible to provide a
specialized stk_param_init function for user-defined covariance
functions. Read stk_param_init if you need to do this. (This feature
might be removed or modified in future releases.)
Radial basis functions (old and new):
stk_rbf_matern, stk_rbf_matern32, stk_rbf_matern52 and
stk_rbf_gauss (previously available internally as stk_sf_*
functions).stk_rbf_exponential, st_rbf_spherical.stk_rbf_matern32, stk_rbf_matern52 return 0 for very large
h, where stk_sf_matern32 and stk_sf_matern52 returned NaN.New covariance functions
stk_expcov_iso, stk_expcov_anisostk_sphcov_iso, stk_sphcov_anisomodel.lm and linear model objects (stk_lm_* classes), introduced as
an experimental feature in STK 2.2.0, are now the recommended way of
setting the linear part of Gaussian process models.
model.order is deprecated (but still supported).
As an example, the following define a Gaussian process with a Matérn 5/2 covariance function and a quadratic trend:
model = stk_model ('stk_materncov52_aniso');
model.lm = stk_lm_quadratic;
stk_lm_polynomial (new function): Create a polynomial model of given
degree, up to cubic models.
stk_model_gpposterior objectsA new stk_model_gpposterior class is introduced to represent a Gaussian
process conditioned by observations (which is again Gaussian process).
Internally, an stk_model_gpposterior object currently stores the QR
factorization of the associated kriging matrix (other representations
will be implemented in the future).
stk_predict is overloaded for stk_model_gpposterior objects.
stk_model_update (new function): Update a model with new observations.
stk_sampling_sobol: New function to generate points from a Sobol
sequence using the algorithm of Bratley and Fox (1988), as modified by
Joe and Kuo (2003). The C implementation under the hood is due to Steven
G. Johnson, and was borrowed from the NLopt toolbox (version 2.4.2).stk_sampcrit_ei_eval (new function): Compute the expected improvement
(EI) criterion for single-objective noiseless optimization.
stk_sampcrit_ehvi_eval (new function): Compute the expect hyper-volume
improvement (EHVI) criterion (Emmerich, Giannakoglou & Naujoks, 2006) for
multi-objective noiseless optimization. This function implements an
exact computation of the EHVI criterion, using a decomposition of the
dominated region into hyper-rectangles.
stk_sampcrit_emmi_eval (new function): Compute the expected maximin
improvement (EMMI) criterion for multi-objective noiseless optimization
(Svenson & Santner, 2010).
stk_pmisclass (new function): Compute either the current probability of
misclassification or the expectation of the future probability of
misclassification, with respect to a given threshold.
stk_dominatedhv (new function): Compute Pareto-dominated hypervolumes,
which relies internally on the "Walking Fish Group" (WFG 1.10)
algorithm. The function can also return the underlying
inclusion-exclusion representation of the dominated region, i.e., its
representation as a collection of signed overlapping hyper-rectangles.
stk_predict_leaveoneout: New function that computes leave-one-out
predictions and residuals.
stk_isnoisy (new function): Returns false for a noiseless model and
true otherwise.
All STK functions related to graphics now accept a handle to existing axes as optional first input argument, and return a handle (or a vector of handles when appropriate) to the graphical object created by the function.
STK is now compatible with Matlab >= R2014b, where handles to graphical objects are not numbers any more.
stk_plot1d: A nice default legend can now be created painlessly using
legend ('show'), and a struct of handles to the graphical objects
composing the plot is returned to facilitate further customization. See,
e.g., examples 1 and 2 in the "kriging basics" series.
stk_plot2d: Removed (had been deprecated for a while).
stk_plot_predvsobs (new function): Plot predictions against observations.
stk_plot_histnormres (new function): Plot histogram of normalized
residuals, together with the N(0, 1) pdf as a reference.
stk_example_doe04: Example script that demonstrates the use of
stk_pmisclass.
stk_example_kb10: Example script that demonstrates the use of
leave-one-out cross-validation to produce goodness-of-fit graphical
diagnostics.
stk_testfun_borehole (new function): New test function (the "borehole
model" response function, from Harper & Gupta 1983).
stk_testfun_twobumps (new function): A simple 1D test function.
stk_dataset_twobumps (new function): Define three datasets based on the
TwoBumps test function.
New overloaded functions for stk_dataframe objects: acos, acosd,
acosh, asin, asind, asinh, atan, atand, atanh, cos,
cosd, cosh, exp, expm1, log, log10, log1p, log2,
logical, sin, sind, sinh, sqrt, tan, tand, tanh.
@stk_dataframe/bsxfun: Now preserve row names if possible.
@stk_dataframe/openvar (new function): Convert stk_dataframe object
to table or double array before opening it the variable editor.
stk_dataframe arrays now accept characters indices (row/column names)
and cell array indices (list of row/column names).
The info field is deprecated.
stk_plot_shadedci: Delete invisible area object.
@stk_hrect/ismember: Optimize for speed.
stk_predict: In the case of discrete models, row input vectors are no
longer accepted.
stk_runtests: Now also available in the Octave package release, to
provide a convenient wrapper around runtestsuite ().
stk_maxabscorr: No longer relies on corr ().
stk_kreq_qr: Now has a default constructor, which allows to load saved
stk_kreq_qr objects properly.
@stk_hrect/ismember: Fix
ismember from working on more than one point at
a time, andB is not an stk_hrect object (it was
incorrectly assumed to be an stk_dataframe in this case).@stk_hrect/subsref: Make sure that the returned value is still an
stk_hrect object when the number of rows (which is two) is unchanged.
Add a clean target to the Octave package Makefile.
Decrease unit test verbosity.
stk_dist, stk_filldist, stk_gpquadform, stk_mindist: Fix segmentation
faults occurring with very large matrices (related to signed
integer-based index computation in the underlying MEX-files).
stk_example_doe03: Use the appropriate flag for maximization.
mole/matlab/file_in_path.m: Fix two bugs (Matlab only)
stk_example_doe03: Display pointwise credible intervals in the upper
panel.stk_param_estim: Fix a bug related to parameter objects. More
precisely, use (:) indexing systematically to access the vector of
numerical parameters corresponding to a given parameter object.
@stk_kreq_qr/get: Fix a call to dot to make it work when there is
only one observation.
Add missing field "Depends" to the DESCRIPTION file in the Octave
package.
stk_param_getdefaultbounds: Return empty lower and upper bounds for
parameter classes that do not implement the stk_param_getdefaultbounds
(instead of calling error).
Add optional field "Autoload" to the DESCRIPTION file in the Octave
package.
stk_optim_hasfmincon: Detect fmincon by trying to use it, instead of
relying on the result of the exist function (ticket #30 closed).
stk_param_estim: Make sure that the bounds that we use for the lnv
parameter contain the starting point lnv0 when it is provided.
@stk_dataframe/set: Fix stk_error calls (missing mnemonic).
stk_distrib_bivnorm_cdf: Fix a bug in the case of mixtures of singular
and non-singular cases.
@stk_dataframe/subsasgn: Preserve column names when deleting rows, even
if the resulting array is empty.
stk_init: Clear persistent variables. As a consequence, stk_init can
now be used to restart STK completely.
stk_commonsize: Accept empty dimensions, under the condition that all
input arguments have the same empty dimensions (in which case the result
is empty).
stk_commonsize: is now faster when some arguments already have the
proper size (unnecessary calls to repmat are avoided).
stk_distrib_normal_cdf, stk_distrib_bivnorm_cdf: are now slightly
faster (unnecessary calls to stk_commonsize are avoided).
lognoisevariance is now considered a mandatory field. For backward
compatibility, a missing or empty lognoisevariance field is interpreted
as -inf. A NaN value in the lognoisevariance field is now interpreted
as meaning that the variance of the noise must be estimated.
model.param is set to NaN by stk_model. This special value indicates
that the parameters must be estimated from the data before any prediction
can be done.
Improved documentation for stk_model.
stk_param_init defaults to using the input value of
model.lognoisevariance if it is not NaN, and estimating the variance if
it is NaN. The meaning of the fifth argument, now called DO_ESTIM_LNV,
has thus slightly changed: it is used to force or prevent the estimation
of the variance of the noise, regardless of the value of
model.lognoisevariance.
stk_param_init also supports the heteroscedastic noisy case, but only
when the variance of the noise is assumed to be known.
stk_param_init_lnv is a new function that provides a rough estimate of
the variance of the noise (in the spirit of stk_param_init).
stk_param_estim estimates the variance of the noise if either
param0lnv is provided and is not empty (as in STK <= 2.2.0), ormodel.lognoisevariance is NaN (new behaviour).If param0lnv is not provided, a starting point is obtained using the
new stk_param_init_lnv function. In all cases (whether lnv is
estimated or not) a meaningful value is returned for lnv (equal to
model.lognoisevariance when lnv is not estimated).
stk_param_estim can provide a value for param0 when it is missing
from the list of input arguments.
stk_param_relik: Compute G = W' * K * W in such a way that the result
is always (?) symmetric.
stk_predict computes lambda_mu and RS only when necessary, depending on
the number of output arguments.stk_noisecov now has a pairwise argument, like the others.stk_sampling_randunif accepts empty dim argument when box is providedstk_generate_samplepaths: Do not add observation noise to the generated
sample paths. This is consistent with stk_predict, which returns
posterior variances for the unknown function, not for future noisy
observations.
stk_conditioning: Simulate sample paths conditioned on noisy
observations when the additional NOISE_SIM argument is provided.
stk_generate_samplepaths: Fix conditioning on noisy observations, which
was not implemented properly until now.
stk_generate_samplepaths: The output is an stk_dataframe object if
either MODEL.response_name exists and is a non-empty string, or one of
the input arguments (XI, ZI, XT) is an stk_dataframe object.
stk_conditioning: The output is an stk_dataframe object if either
LAMBDA or ZSIM is an stk_dataframe object.
stk_hrect: new class to describe hyper-rectangle objects.
stk_boundingbox: constructs the bounding box for a set of points.
stk_example_kb04 demonstrates how it is possible to estimate the
variance of the noise without providing a initial guess for it.
stk_example_kb09 demonstrates how to simulate conditional sample paths
in the case of noisy observations, both in the homoscedastic and in the
heteroscedastic cases.
stk_distrib_bivnorm_cdf computes bivariate normal probabilities.
stk_disp_progress: New function that displays a textual progress
indicator.
stk_feval handles cell-arrays of functions (ticket #19 closed),
multivariate outputs (ticket #20 closed), and uses vectorized calls by
default (unless a progress indicator is displayed).
sort, mtimes, uplus and uminus are now overloaded for
stk_dataframe objects
min, max are now able to return a second output argument (index of
mininizer or maximizer) for stk_dataframe arguments.
Now the output of stk_dataframe is always an stk_dataframe object.
Previously, this wasn't true if the first input argument was, e.g., an
stk_factorialdesign object.
stk_distrib_normal_ei, stk_distrib_student_ei: bugfix (the optional
input argument "minimize" was not taken into account).
stk_distrib_normal_cdf: Fix the zero-variance case.
stk_test and stk_runtests with the Octave packagepkg install.stk_model now also accepts function handles for covariance_type.
stk_ortho_func is deprecated and will be completely replaced, in the
3.x series, by linear model objects. In the meantime, stk_ortho_func
has been kept as a gateway to stk_lm_* functions and now supports the
case of cubic polynomial models.
stk_cholcov: new function that adaptively adds a little bit of noise on
the diagonal of a covariance matrix to help chol succeed, when the
first factorization returned by chol is not complete (a warning is
emitted when doing so). Used in stk_param_init, @stk_kreq_qr/get,
stk_param_relik...
@stk_kreq_qr: heuristic improvement of numerical conditioning
(implemented in the new private function compute_P_scaling).
Accept invRho = 0 in anisotropic covariance functions.
stk_sf_matern: Handle special cases (3/2, 5/2, infinity) explicitly,
and handle large values of the smoothness parameter nu better.
Handle the case of Gaussian isotropic and anisotropic covariance
functions in stk_param_init and stk_param_getdefaultbounds.
Introduce linear models objects. Currently, the following linear model
object classes are available: stk_lm_null, stk_lm_constant,
stk_lm_affine, stk_lm_quadratic, stk_lm_cubic and stk_lm_matrix.
Linear model objects are still considered an experimental feature. They
can be accessed by setting model.order to NaN, in which case model.lm
is expected to contain a linear model object.
stk_example_misc03: New example script that demonstrates the use of
linear model objects.
stk_generate_samplepaths)The simulation of conditioned sample paths has been made easier (see
ticket #3 on SF). This is demonstrated by stk_example_kb08.
Now uses model.response_name (if available) to create column names for
the output array, and xt.rownames (if available) to create row names.
stk_generate_samplepaths can deal with replicated rows in xt.
stk_param_estim
info structure, which currently contains the
criterion that has been used, the criterion value at the optimum, and
the bounds.stk_param_relik
G = W' * K * W and apply a naive fix if it is not
(emit a warning when doing so).n (about 1000, say).New optimization options (can bet set through stk_options_set)
stk_param_estim.optim_display_level option to control the verbosity
fmincon/fminsearch. Its default value is 'off'.stk_param_gls: new function that computes the GLS estimator.
stk_dataframe, stk_factorialdesign)stk_length: New function that returns the "length" of an array,
currently defined as its number of rows.
Improved display for both stk_dataframe and stk_factorial objects
Fix and improve accessors (subsasgn, subsref, set, get,
fieldnames)
Minimalist support for linear indexing on stk_dataframe objects
New overloaded methods: @stk_dataframe/abs, @stk_dataframe/reshape
@stk_dataframe/plot: Full rewrite to improve compatibility with the
base plot function. The case where x is an stk_dataframe objects with
two or more columns is now handled in a way that is consistent with the
base plot function (i.e., if x has two columns, then we get two 1D
plots).
@stk_dataframe/horzcat, @stk_dataframe/vertcat: Now the result is
always an stk_dataframe object, and has row names iff either one of the
two arguments doesn't have row names, or the row names of both arguments
agree.
@stk_dataframe/bsxfun: Modify the behaviour of bsxfun for
stk_dataframe objects. The result is always an stk_dataframe object,
and has column names iff either one of the two arguments doesn't have
columns names or the columns names of both arguments agree.
stk_plot2d is deprecated and will be removed in the 3.x series. Use
contour, mesh, surf... directly instead (they are now overloaded
for stk_factorialdesign objects).
stk_plot1d: Improved flexibility in the way input arguments are
handled.
stk_figure does not set the axis title any more.
stk_isdominated: New function that returns true for dominated rows.
stk_paretofind: New function that finds non-dominated points.
stk_example_misc04: New example script illustrating random Pareto fronts.
Stop bothering users at startup with information that they can find in
the README file anyway.
Don't display selected optimizers at startup.
In Matlab, don't bother checking if the PCT is installed.
New HTML documentation, available in the "all-purpose" Matlab/Octave release (doc/html directory) and online on Source-Forge at http://kriging.sourceforge.net/htmldoc.
Lots of fixes and improvements in help texts.
Add a CITATION file, which explains how to cite STK in publications.
stk_testfun_braninhoo: Fix domain bounds in the documentation.
Options set/get
stk_options_set: Add a reset feature.stk_options_set: Prevent persistent from being cleared (bugfix)Remove page_screen_output (not needed anymore).
Restore the stk_ prefix for distrib_* functions (distrib_normal_cdf
is renamed to stk_distrib_normal_cdf, distrib_student_ei to
stk_distrib_student_ei, etc.)
Lots of internal changes, minor changes, etc. not worth mentioning here.
stk_param_init.Add size checks to several functions.
Warn Octave users about the problem with MEX-files in privates folders:
Octave must be restarted when stk_init is run for the first time.
README or
stk_init.m)Existing examples have been improved: descriptions rewritten; graphical
options controlled globally thanks to dedicated plotting functions
(stk_figure; stk_subplot, stk_axes, stk_title...); + lots of
minor changes
New examples
nuNew function: stk_gausscov_iso (isotropic Gaussian covariance model)
New function: stk_gausscov_aniso (anisotropic Gaussian covariance model)
The precision of stk_sf_matern has been improved around 0 for high nu
New function: stk_sf_gausscorr (Gaussian correlation function in 1D)
New function: stk_phipcrit (phi_p criterion for space-filling designs)
New function: stk_maxabscorr (maximal pairwise absolute correlation)
A new 'probability distributions' module has been initiated (read
misc/distrib/README to understand the reasons why)
Currently provides: pdf, cdf and expected improvement (EI) for the Gaussian and Student t distributions
Matlab/Octave compatibility throughout all supported releases has been strengthened, thanks to the creation of a Matlab/Octave Language Extension (MOLE) module
octave_quantile removed; instead, a replacement for quantile is
provided by the MOLE when needed.
new function graphicstoolkit, providing a kind of replacement for
graphics_toolkit, that also work in Matlab and old Octave releases
...
stk_plot1dsim has been removed (use stk_plot1d instead)
plotting functions now work directly on the current axes
An optional box argument has been added to stk_sampling_halton_rr2
stk_feval now uses input row names for its output
@stk_kreq_qr/stk_update is now (inefficient but) working
isequal is now working for stk_dataframe and stk_kreq_qr objects in
Octave 3.2.x (explicit overloading was required for these old releases)
and many other tiny little things
core/stk_predict.m (related to blockwise computations)Fix a bug in @stk_dataframe/subsref (handle colnames properly when
()-indexing is used to extract a subset of rows).
Fix a bug in @stk_dataframe/stk_dataframe (make sure that .data
contains numerical data) and add a copy constructor.
Fix a bug in stk_predict (don't compute the optional outputs lambda
and mu when they are not requested by the caller).
Fix a bug in stk_sampling_olhs (fail neatly when called with n = 2).
New R-like data structures: @stk_dataframe, @stk_factorial_design.
The structures previously used everywhere in STK (with a .a field) are
still supported but should be considered as deprecated (and will probably
be completely removed in the next major release).
As a result, stk_predict does not return a .a/.v structure any
more. Instead, it returns an stk_dataframe object with two variables
called mean and var.
The function that computes (the opposite of the log of) the restricted
likelihood is now called stk_param_relik instead of stk_remlqrg.
Many improvements in the internal structure of STK, for the sake of clarity (for those who happen to read the code) and efficiency:
@stk_kreq_qr: new class for encapsulating basic computations related to
a Gaussian process (kriging) model.
The old Kx_cache/Px_cache mechanism, for working efficiently on
finite spaces, has been replaced by a new covariance function:
stk_discretecov.
A new framework to encapsulate various approaches to parallel
computations. Currently only supporting 'none' or 'parfor'
(Mathworks' PCT toolbox parfor loops) engines, more to come later.
model.param is now allowed to be an object from a user-defined
class. This feature is experimental, and not really used currently in the
toolbox.
A new function stk_param_getdefaultbounds has appeared in ./param,
that was previously hidden in stk_predict. It can be overridden in the
case where model.param is an object from a user-defined class.
Fill-distance computation: exact (using Pronzato & Müller, Statistics & Computing, 2011) or approximate (using a space-filling reference set).
Van Der Corput and Halton RR2-scrambled sequences (quasi-MC)
NOLHS designs (Cioppa & Lucs, Technometrics, 2007)
misc/options: a new system for managing options
octave_quantile: replacement for the missing quantile function in
base Matlab (Mathworks' Statistics toolbox is not a requirement of STK).
Add MEX-files for computing "Gibbs-Paciorek quadratic forms" to support future work on non-stationary covariance functions.
AUTHORS: a list of maintainers and contributors can now be found at the
root of the source tree.
stk_compile_all: now recompiles MEX-files automatically if the source code
has changed.
Various new utility functions, tiny or not-so-tiny improvements, bugfixes here and there...
stk_predictNow offers the possibility to compute the posterior covariance matrix (it is returned as a fourth optional argument).
Has been modified to work with non-stationary covariance functions.
"pairwise" option to all covariance functions and also to
stk_dist (formerly stk_distance_matrix). This options allows to
compute only the diagonal of the full distance/covariance matrix).New function (stk_filldist) to compute the (discretized) fill distance.
New function (stk_sampling_olhs) to generate Orthogonal Latin Hypercube
(OLH) samples using the algorithm of Ye (1998).
stk_param_init).stk_rescale,
stk_normalize.
Improved the flexibility most functions (stk_predict,
stk_param_estim, ...), which are now accepting both matrices and "data
structures" (with an .a field) as input arguments.
New function: stk_datastruct
New function stk_plot2d that serves has a wrapper around
{surf|contour|mesh|pcolor}-type functions, to plot data defined
over a two-dimensional regular grid.
stk_sampling_regulargrid now also returns 'ndgrid-style' coordinate
matrices stored in new .coord field.
Reorganized the example folder and renamed all example scripts.
New example (stk_example_misc03) to demonstrate the effect of adding a
prior on the covariance parameters.
Improved graphical outputs in stk_example_kb03.
New test function: stk_testfun_braninhoo (Branin-Hoo).
Renamed stk_distancematrix to stk_dist.
Various new utility functions: stk_runexamples, stk_disp_framedtext,
stk_disp_examplewelcome, stk_plot_shadedci, stk_octave_config.
Improved Octave-specific configuration.
Lots of bugfixes and improvements.
New special functions for the Matérn 3/2 and 5/2 correlation functions
(stk_sf_matern32, stk_sf_matern52). New covariance functions
(stk_materncov32_iso, stk_materncov32_aniso, ...).
New MEX-file to compute the separation distance (stk_mindist).
New function to generate random Latin Hypercube Samples
(stk_sampling_randomlhs). Renamed stk_sampling_cartesiangrid to
stk_sampling_regulargrid, and changed the meaning of the first argument
for consistency with other stk_sampling_* functions.
Improved stk_model function. Now provides default parameters for several
families of covariance functions.
Renamed fields in model structures (covariance_cache to Kx_cache and P0
to Px_cache). A new field dim has been added to the model structure.
Changed the order of the arguments of the functions that use the
structure model. Now, model is always the first argument.
Changed stk_param_estim to make it possible to estimate noise variance.
Fixed issues in stk_param_estim related to the definition of the search
domain and the selection of (constrained/unconstrained) optimizer.
Renamed stk_conditionning to stk_conditioning.
New functions for a more flexible and efficient management of STK's
configuration in stk_init (path, compilation of MEX-file, checking for
optional packages, selection of the default optimizer, ...).
New functions for unit testing, based on Octave's testing system
(stk_test, stk_runtests). Tests have been added to most functions in
the toolbox.
Improved documentation & new examples.
Improved argument checking and error messages.
Improved compatibility with older versions of Octave and Matlab.
Lots of minor changes and bug fixes.
Complete reorganization of the code (better directory structure).
Package: stk