This table provides quick access to what's new in each version.
FSDA follows typical MATLAB timetable in the sense that there are two releases per year. The first typically in May/June and the second around October/November.
All up to date files are in the git public repository https://github.com/UniprJRC/FSDA
Version (Release)  New Features and Changes  Version Compatibility Considerations  Fixed Bugs and Known Problems  Release dates 

V8.5.8 (prerelease 2021b) 
ROBUST CLUSTERING Likelihood ratio test inside ctlcurves.m and extended output which automatically detects a set of candidate solutions.
GRAPHICS New function ctlcurvesplot.m to plot the output of the trimmed likelihood curves New function moonplot to show the output of correspondence analysis New function balloonplot to visualize large categorical data DATASETS New datasets oliveoil, wine and flea added to cluster analysis section. New datasets csdPerceptions and mobilephone added to the multivariate analysis section MULTIVARIATE ANALYSIS New function mcdeda which monitors the output of mcd for a sequence of values of breakdown point New option conflimMethodCramerV in function corrNominal to compute the confidence interval of Cramer V coefficient. REGRESSION New options inside AVAS to make it robust to the presence of outliers Sreg and MMreg with hyperbolic tangent estimator made faster. New options inside LTSts and simulateTS that allow a customized definition of the autoregressive component
UTILITIES Added weights in repDupValWithMean.m New function setdiffFS in case input arguments just contain positive integer values. 
In a
lot of functions the instruction coder.target('MATLAB') appears in
order to cope with the MATLAB C coder requirements. We stop supporting releases before 2016b. 

The offical expected release date is October 2021 
V8.5.4 R2021a 
MULTIVARIATE ANALYSIS New function pcaFS which enables to visualize both the percentage of variable explained by the different components, both the factor loadings and interactive dynmic biplot. New function biplotFS which enables to call the app biplotAPP which creates an interactive dynamic biplot.
Improvements in functions spmplot (now input can also be a table) and CorAna (now input can also be a table when optional option datamatrix is true) CORRESPONDENCE ANALYSIS A new suite of functions for robust correspondence analysis. Functions mcdCorAna, FSCorAnaeda, FSCorAnaenvmmd and mahalCorAna, extend functions mcd, FSMeda, FSMenvmmd and mahalFS to the context of contingency tables. The plots produced by functions malindexplot and malfwdplot have been modified to incorporate the output of these new functions.
GRAPHICS New function barVariableWidth which produces a bar plot with different widths and colors for each bar In functions mmdplot, mdrplot, mmdrsplot and mdrrsplot added the possibility of showing in output arguments the list of units brushed in each brushing operation Option tag added to FSR, FSRmdr, FSM, FSMmmd, FSRts, FSRB, FSRr and FSRH Option label added to malindexplot
ROBUST CLUSTERING newoption warmup in tclustICgpcm new option commonslope in tclustreg and tclustregeda and tclustregIC
DATASETS New dataset citiesItaly added to multivariate analysis section.
REGRESSION New options for VIOM and MSOM contamination inside function simulateLM
STATISTICAL UTILITIES Added a series of routines for the estimation of integrated and instantaneous variance of a diffusion process via Fourier analysis [M.E. Mancino, M.C. Recchioni, S. Sanfelici, ``FourierMalliavin Volatility Estimation. Theory and Practice'', 2017, Springer  New York] FE_int_vol, FE_int_vol_Fejer, FE_splot_vol, FE_spot_vol_FFT, CEVmodel, OptimalCuttingFrequency
GUIs A new set of functions which enable to monitor all the necessary steps to be done to obtain the main indexes of descriptve statistics. More in detail: GUIconcentration, GUImad.html, GUIpowermean.html, GUIquantile.html, GUIskewness.html, GUIstd.html, GUItrimmean.html, GUIvar.html, GUIcov.html, GUIregress.html

Routines pcaFS
and biplotFS assume
that at least MATLAB 2019b is installed. We stop supporting releases before 2016a. 
Starting from MATLAB 2021a in order to view the FSDA html documentation it is necessary on the Home tab, in the Environment section, click Preferences. Select MATLAB > Help and change the Documentation Location. In this case select option "installed locally". 
March 2021 
V8.3.0 (R2020b) 
TRANSFORMATIONS IN REGRESSION We have enriched the properties of the data transformations of the Yeo and Johnson (2000) for negative and positive responses, which we introduced in R2020a. More specifically, we intervened on the smoothness condition that the second derivative of zYJ(lambda) with respect to y be smooth at y = 0, along Atkinson et al (2019) and (2020), to allow two values of the transformations parameter: lambdaN for negative observations and lambdaP for nonnegative ones. Now, function ScoreYJall computes: 1) a global t test associated with the constructed variable for lambda=lambdaP=lambdaN. 2) a t test for positive observations. 3) a t test for negative observations. 4) a F test for the joint presence of the two constructed variables described in points 2) and 3. 5) the F test based on the maximum liklihood estimate of lambdaP and lambdaNNew function ScoreYJall which computes the score tests described in points 1)5) above. New function scoreYJmle which computes, in the case of extended Yeo and Johnson transformation, the likelihood ratio test of H0: lambdaP=lambdaP0 and lambdaN=lambdaNeg0. Added option usefmin in funtion boxcoxR. This option uses the solver (fminsearch or fminunc) to find MLE of the two transformation parameters for extended Yeo and Johnson family (Atkinson et al. 2020). New function fanBIC which takes in input the output of FSRfan and using BIC and smoothness index enables to automatically choose in an efficient and robust way, the best value of the transformation parameter. New function fanBICpn which enables to automatically choose the best values of the transformation parameters for positive and negative observations New function normYJpn which extends the companion functions normBoxCox and normYJ to the case of extended Yeo and Johnson transformation. TIME SERIES New function SETARX which implements Threshold autoregressive models with two regimes ROBUST CLUSTERING New tools for dealing with the 14 Gaussian parsimonious clustering models (GPCM). In function genSigmaGPCM new option pa.exactrestriction has been added. If pa.exactrestriction is true the covariance matrices are generated with the exact values of the restrictions specified in pa.cdet, pa.shw and pa.swb. In function MixSim optional input structure sph now can be called with field sph.exactrestriction In function tclust the
fourth input restrfactor can be a structure which can contain the
type of Gaussian Parsimonious Clustering Model  GPCM (restrfactor.pars),
the New functions tclustICgpcm, tclustICsolGPCM, tclustICplotGPCM, and carbikeplotGPCM which extend functions tclustIC, tclustICsol, tclustICplot and carbikeplot to the case of the 14 GPCM. GRAPHICS New plots waterfallchart
(which implements the waterfall chart (see
https://en.wikipedia.org/wiki/Waterfall_chart) and new function
funnelchart which implements the
funnel chart (see new function scatterboxplot (which creates scatter diagram with marginal boxplots). Improvements to functions Now spmplot accepts as input a table. In the case the names of the tables are automatically added at the margins. Similarly, in function corrNominal when option datamatrix is true it is possible to supply as first argument a table.
DATASETS New datasets balancesheets and facemasks added in the datasets regression section and datasets clustering section respectively 
We stop supporting
releases before 2015b. Functions FSRfan, ScoreYJ and ScoreYJall made faster 
Mathworks
search engine in our HTML web pages in version 2020b works again. Routines fanBICpn, tclustICgpcm and tclustICplot gpcm use routine heatmap introduced in MATLAB 2017a. Routine tclustregeda to display the results uses function parallelplot introduced in Matlab 2019a. 
October 18th 2020 
V8.0 (R2020a) 
ROBUST REGRESSION New set of routines for minimum density power divergence estimators (mdpd, mdpdR, mdpdReda, PDrho, PDpsi, PDwei, PDpsider, PDpsix, PDbdp, PDeff, PDc ), discussed in https://www.mdpi.com/10994300/22/4/399) New function simulateLM to simulate linear regression data with prespecified value of R2, prespecified correlation among the explanatory variables and type of distribution. New function VIOM which computes weights estimates under a VarianceInflation Outlier Model using MLE or Restricted MLE (REMLE). ROBUST CLUSTERING New function tclustregeda which enables to monitor the regression clustering classification for different levels of trimming. Improved function tclustregIC which enables to compute the BIC (and other information criteria) for different values of restriction factors and different number of groups, for classification or mixture likelihood and regression clustering. Modified function tclustICsol now accepts input from tclustregIC to show the yXplot of the best solutions. New function ctlcurves to select the appropriate number of groups in robust clustering. New function mdrrsplot which plots the random starts trajectories and enables to brush them. The companion function mmdrsplot referred to multivariate analysis has been improved.
TRANSFORMATIONS IN REGRESSION New function boxcoxR which
computes the profile log Likelihood for a range of values of the
transforamtion parameter (lambda) and computes the MLE of lambda in
the DOCUMENTATION Improved menu for the automatic installation of the FSDA html help files. UTILITIES New function exactcdf for finding the exact cdf of each element in a vector x with respect to the empirical distribution, represented by another vector. New functions twdpdf and twdrnd to compute the pdf of the Tweedie distribution and generate random numbers from it.

We stop supporting
releases before 2015a. Functions PoolPrepare.m and PoolClose.m removed (not necessary with the latest releases of parallel computing toolbox). Cleaner code for tclust and tclultreg functions now available; the core part which computes the EM algorithm for each subset which is extracted, is now in tclustregcore.m and tcluscore.m; these two functions are internal and therefore undocumented. From this release we support older releases up to 2015a (however about 85% of the FSDA still runs with older versions of MATLAB up to 2012a). 
Mathworks
search engine in our HTML web pages in version 2020a does not work
anylonger. To search for FSDA function it is necessary to use the supplemental software search engine. Corrected small bug in LTSts in case of level shift with very small series. 
April 2020 
V7.1 (R2019b) 
This is the first release which is distributed from Mathworks marketplace and from github platform. TRANSFORMATION IN REGRESSION New function tBothSides which enables to transform both sides of a (nonlinear) regression model. New function boxcoxR which finds MLE of lambda in linear regression (and confidence interval) using Box Cox or Yeo and Johnson family. ROBUST TIME SERIES ANALYSIS New functions LTStsVarSel.m which enables to perform variable selection in the robust time series model LTSts.m. In functions LTSts.m, simulateTS.m and forecastTS.m it is now possible to add an autoreressive component. UTILITIES New function existFS which checks whether a file exists and puts the answer in a cached persistent variable DOCUMENTATION Added file getting_started.mlx in subfolder doc of the main root of FSDA for packaging the FSDA toolbox,

From this release we
support old
releases up to 2014b. Now functions tclust.m and logmvnpdfFS.m do
not need anymore the presence of MEX files. This modification has
been made necessary because at present Mathworks toolbox packaging
does not support mex files. 
Fixed a bug in
tclutICplot New function startup.m has been added to the main folder of FSDA which copies all HTML documentation files in subfolder (FSDA root)/helpfiles/FSDA into (MATLAB docroot/help). The files can be copied in Windows system just if the user has administrator privileges. 
October 2019 
V7.0 (R2019a) 
CLUSTER ANALYSIS Function tclustreg has been considerably enhanced. Now the function includes: (i) robust BIC, (ii) possibility of constraining the determinants of the covariance matrices of the explanatory variables, (iii) options for treating datasets with concentrated noise, making use of concentration steps appropriately modified using observation weighting and thinning methods. New function tclustregIC which (if present) uses the Parallel Computing toolbox to compute robust BIC for mixture and classification likeilhood for different values of k (number of groups) and different values of c (restriction factor for the variances of the residuals), for a prespecified level of trimming. New function for constraining the determinants restrdeter. This function has its own interest but is called in every concentration step of function tclust in case determinant restriction is needed. Routines for constraining the determinants (restrdeterGPCM), the shape matrices (restrshapeGPCM) and to impose common rotation matrices (common principal components) in presense of equal shape (cpcE.m) or varying shape (cpcV.m) and a general routine to impose constraints in the family of the 14 Gaussian Parsimonious Clustering Models (restrSigmaGPCM). Routine to generate data based on the 14 Gaussian Parsimonious Clustering Models (genSigmaGPCM). This routine can be called directly from function MixSim in order to generate each of the 14 Gaussian Parsimonious Clustering Models with a prespecified level of overlap (see option sph inside MixSim). Routine GowerIndex to compute matrix of similarity indexes using Gower metric. DATASETS New datasets added to the collection: animals, P12119085, P17049075, fondi_large, JohnDraper data, gasoline data, ms212. See pages datasets_reg and datasets_mult for a description of these datasets. GRAPHICS Possibility of brushing using rownames. Rownames also appear in the associated scatter plot matrix, both for regression and multivariate analysis: se new examples in resfwdplot and malfwdplot. New function aceplot to visualize the results of the output produced by functions ace and avas. Option RowNamesLabels has been added to add2spm and to add2yX to label the units. MULTIVARITATE Funciton FSMeda is now much faster; the original function FSMeda has been kept, renamed FSMedaeasy, because the algorithm is much easier to follow. REGRESSION New functions: (i) ace which implements the alternating conditional expectations algorithm to find the transformations of y and X that maximise the proportion of variation in y explained by X and (ii) avas which uses a (nonparametric) variancestabilizing transformation for the response variable. New function smothr to smooth values imposing variour constraints (e.g. monotonicity, circularity,..). This function calls the supersmoother routine of Friedman. New function rlssmo to compute a running line smoother with global cross validation. New function supsmu to smooth scatterplots using Friedman's supersmoother algorithm. Function RobCov now includes the estimator covrobc (a corrected version of the covariance matrix of robust beta coefficients). A new motivating example shows a case why covrobc should be always used. UTILITIES New function repDupValWithMean that enable to replace values of y including non unique elements in vector x with local means. UTILITIES HELP Function publishFS is fourthly improved. This function automatically transforms structuerd .m files into MATLAB pure style files. In the HTML help files now the right click of the mouse (similarly to pure Mathworks pages) enables to execute, select or find help (F1 key) for all the versions of MATLAB starting from 2017a.
STATISTICAL UTITLIES New function genr8 to generate random numbers which are coherent across different software platforms. New function exactcdf to find exact cdf values of each element of an input vector x with respect to an empirical distribution. New function wthin which thins a uni/bidimensional dataset. New function ctsub which computes numerical integrarion from x(1) to z(i) of y=f(x) New functions (i) vervaatsim
(to simulate precisely from a Vervaat perpetuity

This is the last
release where we we support old
releases up to 2012a. 
Fixed a bug in
mtR when the user wanted to continue the simulation using a negative
seed 
May 2019 
V6.1 (R2018b) 
(1) New function qqplotFS that enables to create a qqplot of residuals with confidence bands (2) New function mtR which generates the same random numbers produced by R software with Mersenne Twister mt19937ar (3) New functions associated with Rocke biweght estimator. See for example RKrho, RKpsi, RKpsider, RKwei, RKbdp, RKeff. (4) Routines FSR, FSRmdr, FSRbsb extended to time series (see new functions FSRts, FSRtsmdr, FSRtsbsb and regressts) (5) New function verlessthanFS. It is a faster version of MATLAB function verlessthan. (6) New datasets added to the collection. (7) New routine publishBibliography to create in a automatic way the bibliography from the citations present inside the .m files. 

Fixed a problem
in the brushing from spmplot and on the diagonal there are the
boxplots. See for more details the additional examples in yXplot and
spmplot. Improved option for thinning units inside tclustreg Solved minor bug in FSM when it was called with option 'bonflev' 
September 2018 
V6.0 (R2018a) 
(1) New function tclusteda that helps choosing the best tclust model. It computes tclust for different values of the trimming factor and produces plots that allow to find the optimal level of trimming. This function uses the parallel processing toolbox, if available. (2) Extension of the score test. New function ScoreYJpn that computes the score test for Yeo Johnson transformation separately for positive and negative observations. FSRfan now accepts the new option family "YJpn" and it is possible to monitor the score test for both positive and negative observations (output arguments out.Scorep and out.Scoren). (4) New functions for time series analysis. simulateTS simulates a time series with trend (up to third order), seasonality (constant or of varying amplitude) with a different number of harmonics and a level shift. forecastTS produces forecasts with confidence bands for a time series estimated with function LTSts. (4) CorAna has an improved display of results. New function CorAnaplot draws a rich Correspondence Analysis graph with different types of confidence ellipses for selected rows and columns. (5) New function verlessthanFS. It is a faster version of MATLAB function verlessthan. (6) Documentation of yXplot considerably improved. New options added (xlimx, ylimy, namey, nameX). (7) MixSimreg extended to account for multiple parameter distribution (betadistrib option) (8) histFS has a new optional argument (weights) for plotting a weighted histogram. (9) options labenv has been added to mmdrsplot. (10) option axesellipse added to ellipse (11) New output argument idxMapping used in function ClusterRelabel, to track the indexes permutations used to rearch a desired cluster labelling. 
From release 2018a we support old
releases up to 2012a. From 2018a the use of subfunctions tinvFS, finvFS, tcdfFS, fpdfFS, fcdfFS which compute inverse, pdf, cdf of the T and F distribution are not supported anymore. Following the feedback provided by our users, Function UnitsSameCluster (which was introduced in R2017a) has been renamed (for better readability) ClusterRelabel 
Fixed a series of problems associated to MATLAB 2018a. For example now empty variables which will contain numbers have been initialized with [], while empty variables which contain characters are initialized with ' '. See for example functions yXplot and spmplot.  May 2018 
V5.1 (R2017b) 
FSDA has introduced two new categories of tools, one for (robust) time series analysis; another for analyzing categorical data and contingency tables. More precisely:
(1) Function LTSts
extends LTS estimator to time series. A related new graphical plot
associated to a time series,
wedgeplot, provides information on the presence
of outliers and level shifts. (2) CorAna performs correspondence analysis; SparseTableTest computes independence test for large and sparse contingency tables; CressieRead computes the power divergence family of tests, to check the discrepancy/distance between observed and expected frequencies in a contingency table; rcontFS generates a random twoway table with given marginal totals; barnardtest computes the Barnard test, corrNominal measures strength of association between two unordered (nominal) categorical variables. Similarly for ordinal data with corrOrdinal. crosstab2datamatrix recreates the original data matrix X from contingency table N. This group of functions is complemented by file examples_categorical.m as in style of FSDA.
The two categories of functions will be progressively enriched.
Other new functions which are included are boxtest (test of equality of covariance matrices used for example in tkmeans), GYfilt (Gervini and Yohai, univariate outlier identifier), mmdrsplot (interactive plot of the trajectories of minimum Mahalanobis distances from different starting points), overlapmap to plot the ordered pairwise overlap values between components, dempk to perform a merging of components found by tkmeans, ncpci to compute a non centrality parameter confidence interval. Finally, spmplot has been enriched to superimpose ellipses, density and contour functions to data and extract single panels from the scatter matrix. 
Various inconsistencies in the browsing of the documentation pages and the bibliography have been fixed.  November 2017  
V5.0 (R2017a)  CLUSTERING Function tclustreg now includes trimmed Cluster Weighted Restricted Models. New function tclustIC for the automatic
selection of the best number of groups. STATISTICAL UTILITIES New routines for density estimation and thinning, for univariate and bivariate data (used in tclustreg). bwe, rthin,
wthin, WNChygepdf UTILITIES

Control version added in many graphical
routines to take account the modifications in MATLAB 2017a
From MATLAB R2012a callback functions started to use new internal data structures. Interactive plots that use such callbacks (e.g. those in GUI brushRES) may produce errors in releases older than R2012a. The issue should be now fixed. Please report to us any problem you may experience. 
May 2017  
V4.1 (R2016b)  New functions for bivariate density
estimation and random thinning (kdebiv.m,
rthin.m) used to extend tclustreg.m features. The FSDA help folder now contains XML files associated to the functions documentation. This is in view of generating/updating automatically or using a GUI the functions documentation, in html as well as in the function head. New html documentation generated with publishFS. 
We are monitoring possible compatibility
issues that may emerge from changes in the tagging policy of the graphical
objects in MATLAB. 
add2spm modified to take into account
a change in the property name of the legend object introduced in MATLAB
R2016b (LegendPeerHandle is now called LayoutPeers). A change in MATLAB R2016b function legend.m was affecting FSDA function add2yX (the legend was plotted twice). Bug fixed. Bug affecting FSMeda only in the univariate case fixed. 
October 2016 
V4.0 (R2016a)  Major release. New function, publishFS, introduced to generate documentation pages directly from the .m files. New function, makecontentsfileFS, introduced to create a the list of files present in a FSDA folder and/or subfolders. It extends MATLAB function makecontentfilesFS. .mlx files introduced for examples_multivariate and examples_regression. New features added to the tclust function, including determinant restriction and new adjusted BIC criterion for the estimation of the number of groups. Added functions for reweighting FSR and FSRB (FSRr and FSRBr). Functions FSR, FSRB and FSRH redesigned; a routing implementing the core of the Forward Search algorithm (FSRcore) introduced to avoid code redundancies. New function, winsor, to winsor data. New function FSMbsb, which will replace FSMbbm. New function randindexFS, to evaluate the quality of different clusterings. New routines poolClose and poolPrepare introduced to conveniently open and close a pool of parallel workers. Several new robust functions to generate, for example, the Tukey Biweigh rho function (HUrho), the tuning constant associated to a certain efficiency (HUeff), the psi functions (HUpsi), its derivative (HUpsider), etc. For a full list, see functions under utilities_stats folder. 
Documentation made compatible with
the new MATLAB help navigation and browserstyle, which was redesigned
in release R2015b. 
Many small bugs fixed. Functions affected
include tclust, tclustReg, position, MixSimReg. ClickableMultiLegend made compatible with R2016a. drawnow command introduced in several graphical functions, to solve episodic bugs in the generation of the plots. 
May 2016 
V3.1 (R2015b) 
Major release.
Function simdataset.m modified to allow the user to simulate outliers from different distributions and contamination schemes and/or contaminate existing datasets. New Bayesian regression analysis routines: FSRB.m, FSRBeda.m, FSRBmdr.m, regressB.m. In FSReda.m: monitoring of confidence intervals of beta and sigma2. In FSRBeda.m: monitoring of HPD (highest posterior density regions) of beta and sigma2. New functions for inverse gamma computation: inversegampdf.m, inversegamcdf.m, inversegaminv.m. Added functions to monitor units forming subset in heterosckedastic and Bayesian regression: FSRHbsb.m, FSRBbsb.m. Added new datasets for Bayesian examples. FSMtra.m: added option for the robust transformation in the YeoJohnson family. addFSDA2path.m: modified for compatibility with unix platforms and to address changes in the folder organization of FSDA functions. Added routines to compute and visualize robust bivariate boxplot (function boxplotb.m) New routine for automatic outlier detection in heteroskdastic regression (FSRH.m) 
In function spmplot, the multiple histograms (boxplots) on the main
diagonal of the scatter plot matrix is now working also with R2015a
and R2015b.
The html documentation pages of some new functions are missing. As a consequence, some links may be broken. New complete documentation, produced automatically from the documentation in the head of our mfiles, will be released soon. 
September 2015  
V3.0 (R2015a) 
Major release.
Added robust regression (tau) and multivariate estimators (StahelDonoho).
Functions taureg.m and SDest.m. New weight functions (hyperbolic, Hampel
and optimal). 
Documentation made compatible with the new help system introduced with MATLAB R2015a 
In function spmplot, the multiple histograms (boxplots) on the main diagonal of the scatter plot matrix do not work with R2015a because of recent changes in gplotmatrix. 
February 2015

V2.1 (R2013a) 
New very fast implementation of the Forward Search for multivariate
analysis (FSMmmd). Forward Search in regression
modified to deal with the cases in which in a particular step of the
search subset is not full rank (FSR and
FSRmdr). New scatter plot matrix with multiple
groups and multiple boxplots on the main diagonal (spmplot). 
Structure modified for compatibility with MATLAB R2012b to R2013a releases. Three APPs introduced in release R2013a. 

May 2013

V2.0 (R2011b) 
Major release. Traditional robust estimators added including S, MM,
MCD, MVE, (Sreg, Smult,
MMreg, MMmult,
mcd, mve) and univariate
and bivariate analysis (unibiv). New interactive
plots and interactive graphics features. 
Redesigned the definition of many optional input parameters in terms of structures 

September 2011

V1.1 (R2010b) 
Multivariate data analysis routines have been added. Function
resfwdplot considerably improved. 


September 2010

V1.0 (R2010a) 
 
A few functions use ~ to denote unused output parameters as from release 2009b 

February 2010
