
Changes in version 1.30.0:

  o Nex fct EPtest
  o New fct johnsonshap() (Warning: does not work yet)
  
Changes in version 1.29.0:

  o New fct johnson()
  
  o Bugs corrected in testHSIC.R concerning some functions' names
  that have been renamed

Changes in version 1.28.1:

  o Bug corrected in fct parameterSets()

  o Bugs corrected about all the ggplot.xxx() fcts issues (required by CRAN)
  
  o Correction in the tell() fct of sensiHSIC() for direct call

Changes in version 1.28.0:

  o New fct correlratio()
  
  o Many bugs corrected in fct sensiHSIC()
  
  o Many additional options added in fct sensiHSIC(), especially HSIC-ANOVA indices
  
  o New fct testHSIC() for independence testing based on HSIC indices
  
  o New benchmark matyas.fun() added in "testmodels.R"

Changes in version 1.27.1:

  o Adding the topic of 'interpretability of machine learning models' 
  in the description of the package

  o emvd() fct and names have been changed to pmvd()

  o Several bugs corrected in pme_knn()
  
  o R requirements: Changes from 'class()' to 'inherits()' in several fcts
  
  o Corrections in parameterSets(), 
  see https://github.com/cran/sensitivity/pull/2
  
Changes in version 1.27.0:

  o New fct pme_knn() for proportional marginal effects computation
  
  o Addition of an example about visualiz. of perturbed law in PLI() fct
  
Changes in version 1.26.1:

  o Simplification in shapleyBlockestimation.R and 
  parameter values changes in shapleyBlockestimation.Rd
  
  o extract and ggplot functionalities added in shapleysobol_knn() fct
  
  o new examples for nice visualizations (via plotCI() of plotrix package)
  in fcts PLIquantile(), PLIsuperquantile(), PLIquantile_multivar() 
  and PLIsuperquantile_multivar()
  
Changes in version 1.26.0:

  o New function shapleysobol_knn() which allows optimized and parallelized 
  computations of Shapley effects/Sobol' indices using the 
  nearest-neighbors method. This fct also replicates the same functionalities 
  than sobolshap_knn() that will be removed in a future package's version
  
  o \donttest examples have been changed in the .Rd of several functions 
  in order to shorten their execution (because the tests are judged too long
  by CRAN)

  o Bug corrected in all PLIxxx() fcts:
    - conditions (delta != 0) replaced by conditions (delta != mu), 
    mu being the input mean)
    - pti=phi(lambda[K]) is not recomputed at each bootstrap iteration 
    (causing numerical instabilities)
  
  o Bug corrected in PLIquantile_multivar() and PLIsuperquantile_multivar()
  fcts (conditions "|" instead of "&")
  
  o Correction in docs of PLIquantile_multivar() and 
  PLIsuperquantile_multivar() to precise that the delta are perturbed means
  
  o In the fct shapleyPermrand(), the test about 'Multiserver queue model'
  has been suppressed (unsolved bug in Xset)

Changes in version 1.25.0:

  o New function PLIsuperquantile_multivar()

  o Bootstrap added in PLIquantile_multivar()
  
  o Bug corrected in weightTSA() (data structures)
  
  o Change in lmg(): new \code{max.iter} argument to increase the maximum
  number of iterative optimization step for logistic regression
  
  o Change in emvd():
	  - new \code{max.iter} argument to increase the maximum number of 
	  iterative optimization step for logistic regression
	  - new \code{tol} argument to detect spurious variables
	  - faster implementation
	  - recursive emvd computation can now be partially done in parallel 
	  
	o Add an example with Gaussian inverse transforms in PLI() fct

Changes in version 1.24.1:

  o Bug for y format in lmg() and emvd(): allow dataframe
  
Changes in version 1.24.0:

  o New function lmg() for LMG sensitivity indices

  o New function emvd() for E-MVD sensitivity indices
  
  o Package foreach is necessary (Imports)
  
Changes in version 1.23.1:

  o Bug of tests of sensiHSIC()
  
  o Bug in sobolshap_knn() (matrix option in argument U)
  
Changes in version 1.23.0:

  o New function qosa() computing quantile-oriented sensitivity analysis
  via the contrast-function formulation

  o Corrections in sensiHSIC() for 
    - taking into account categorical inputs (and the choice of their 
    hyperparameters)
    - taking into account multiple outputs when some are categorical 
  
  o Corrections in sobolshap_knn() for taking into account categorical  
  inputs 
  
  o Correction in bootstats() relative to the use of sobolrep() fct
  
Changes in version 1.22.2:

  o Correction in PLIsuperquantile() for "bias=TRUE" & "type=VAR" case
  
  o New toy function in testmodels(): Friedman function
  
  o New argument 'varoutput' in delsa() in order to be able to
  take the output variance as the empirical variance from the sample
  
  o New argument 'randperm' in sobolshap_knn() in order to use or not
  random permutations to estimate Shapley effects
  
Changes in version 1.22.1:

  o Correction in sensiHSIC.R with test.method = "No" in order to
  not perform the statistical tests
  
  o Correction in nested.cpp

  o Change of colors in shapleyBlockEstimation.Rd
  
Changes in version 1.22.0:

  o New function shapleyBlockEstimation()
  
  o New functionalities in sensiHSIC(): PCA, kernel for categorical 
  inputs and/or outputs, optimization of permutations numbers,
  convergence plot for p-values, U-stat estimator for conditional HSIC
  
  o Corrected plot with new fct plotMultOut() (for ubiquitous Sobol' 
  indices) in sobolMultOut() and associated sobolxxx() fcts
  
  o New bootstrap process in PLIquantile() and PLIsuperquantile() via 
  the new argument bootsample
  
Changes in version 1.21.0:

  o New function sobolshap_knn() (sensitivity analysis via 
  ranking / nearest neighbours)
  
  o New functionalities in sensiHISIC(): aggregated HSIC
  
Changes in version 1.20.0:

  o New functions sobolrep() (Sobol' indices estimation based on 
  replicated orthogonal arrays) and sobolrec() (Recursive estimation 
  of Sobol' indices), which use the new functions addelman_const(),
  discrepancyCriteria_cplus() and maximin_cplus() (discrepancy and
  maximin criteria using a C++ implementation)

  o bootstrap implemented in sobolrank()
  
  o New function shapleyLinearGaussian() which computes Shapley effects
  for linear models with Gaussian inputs
  
  o bug corrected in shapleySubsetMc() with the modified line:
    cost=sum(apply(U,1,function(u) round(Ntot/choose(p,sum(u))/(p-1))))

Changes in version 1.19.0:

  o New author Sebastien Da veiga
  
  o New function sobolrank()
  
  o Functions src() and pcc() adapted to work with logistic GLM model
  (via the new argument logistic = TRUE)
  
  o New argument 'title' in ggplot.shapleyPermRand and
  ggplot.shapleyPermEx
  
  o bug solved in shapleyPermEx() in order to compute the CI for the 
  full first order and independent total Sobol' indices
  
  o New argument 'noise' to consider noisy observations in 
  shapleySubsetMc()

Changes in version 1.18.1:

  o New argument semi (= TRUE or FALSE) in function pcc() in order
  to compute semi-partial correlation coefficient (SPCC)
  
  o bug (caused by new R version 4.0.0) solved in:
    - sobolmartinez.R, base.R, morris.R, morris_oat.R and simplex.R
    (matrix objects now also inherit from class "array")
    - sobolMultOut.Rd, testmodels.Rd and delsa.Rd (screen devices 
    x11() should not be used in examples)
  
Changes in version 1.18.0:

  o New function: weightTSA.R in order to perform Target Sensitivity 
  Analysis by transforming the output sample using  aspecific weight 
  function
  
  o Improvements in sensiHSIC(): 1) for the parameters estimation via 
  the new argument crit.option, 2) for a sequential estimation of the
  pvalue (independence test based on permutations), 3) new argument
  target in order to perform Target Sensitivity Analysis
  
  o New argument 'bias' in PLIsuperquantile(): "TRUE" gives the 
  previous computation; "FALSE" corrects this computation (the sample 
  points were not weighted by the likelihood ratio when computing the 
  perturbed superquantile)

Changes in version 1.17.1:

  o bug (caused by new R version 4.0.0) solved in morris_oat.R
  (matrix objects now also inherit from class "array")
  
  o exception "multiIndex[inputIndex] == 0 & der" solved in 
  PoincareChaosSqCoef.R
  
  o example with given data in sensiHSIc()
  
Changes in version 1.17.0:

    o New functions: squaredIntEstim.R and PoincareChaosSqCoef.R
    (which allows to compute the squared coefficients in 
    generalized chaos via Poincare differential operators)
    
    o Modification in PoincareOptimal.Rd concerning the 
    returned eigenvalues

Changes in version 1.16.3:

    o Unresolved matrix/array classes related bug on R4.0.0 version
    in morris.R, morris_oat.R, soboljansen.R, sobolmartinez.R
    and sobolroalhs.R
    Examples that do not work have been put in \donttest{} (these
    examples work in practice)
    
    o Resolved bug in plot.soboljansen() and plot.sobolmartinez
    when dealing with matrice-type model outputs
    
    o ylabel changed (from S to PLI) when plotting PLI examples
    
    o legends precised (between full and independent Sobol' indices) 
    when plotting Shapley effects

Changes in version 1.16.2:

    o   New functionalities in sensiHSIC() function
    (statistical tests of independence)
    
    o Graph legends corrected in sensiHSIC(), sensiFdiv(), sb() and
  sobolMultOut() functions
  
    o   Corrected bug in nodeggplot()
    
Changes in version 1.16.1:

    o   New function nodeggplot() (in order to ebautify the plots) 
    
    o   ggplot functions for the following functions:
    pcc, src, sensiFdiv, sensiHSIC, shapleyPermEx, shapleyPermrand,
    sobol, sobol2002, sobol2007, sobolEff, soboljansen, sobolmara, 
    sobolmartinez, sobolMultOut, sobolowen, sobolroalhs, sobolroauc,
    sobolsalt, sobolTIIlo, sobolTIIpf, soboltouati
    
    o   Functions sobolroalhs() and sobolSalt(): Modifications of 
    plot functions in order to have "XiXj" instead of "Xij""

    o   New output of function delsa(): Brute values of derivatives

    o   Test case corrected in pcc.Rd

Changes in version 1.16.0:

    o   Added functions for calculating Shapley indices from data: 
    shapleySubsetMC()
    
    o   Added functions for calculating PLI: PLIsuperquantile() and
    PLIquantile_multivar()
    
    o In the 3 PLI functions related to quantiles:
      - new arguments in order to have the PLI in percentage
      - the result also contains the perturbed quantiles values
      - bootstrap confidence intervals can be obtained
    
    o   Added the toy function heterdisc.fun()
    
Changes in version 1.15.2:

    o   Added functions for Morris method for multidimensional outputs:
    morrisMultOut()
    
    o   Added the toy function linkletter.fun()
    
    o   Change the names of the fcts (dtnorm, ..., dtgumbel, ...) by 
    (dnorm.trunc, ...) (reverse dependency pb with ATmet package).
    Export now the fcts, documentation entries in truncateddistrib.Rd
    
    o   Corrected bug: Replace \dontrun by \donttest in all Rd-files
    
    o   Corrected bug: package triangle is suggested and called in 
    PoincareOptimal.Rd
    
    o Function in sobolGPmethods.R and sobolpickfreeze.R have been 
    integrated in sobolGP.R
    
    o   Detected bug (not corrected) in tell.sobolGP() 
    Unused argument in km(), passed by eval(), update(), tell.sobolGP() ??)

    => comment in the example of sobolGP.Rd
    
Changes in version 1.15.1:

    o   Functions shapleyPermEx() corrected (confidence intervals)

Changes in version 1.15.0:

    o   Function "sobolCert.R" has been (temporarily) suppressed
    (compilation bug unresolved)
    
    o   Function "support.R" has been changed by O. Roustant (new plotting
    functionalities are available, as the function "scatterplot")
    
    o   Resolved bug about "sobolmartinez" method (now suppressed) in 
    the sobolMultOut() function

    o   sobolMultOut() now returns the functional Sobol' indices via
    the attributes "Sfct" and "Tfct" of the output object

Changes in version 1.14.0:

    o   Added functions for calculating Shapley indices: shapleyPermEx()
    and shapleyPermRand()

    o   Added function for calculating first order Sobol' indices via
    smoothing technique: sobolSmthSpl()