FSDA

Robust regression, robust multivariate analysis, robust classification and much more...

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Flexible Robust Statistics Data Analysis

This project hosts the source code to the original MATLAB FileExchange project and is place of active development.

FSDA Toolbox™ provides statisticians, engineers, scientists, researchers, financial analysts with a comprehensive set of tools to assess and understand their data. Flexible Statistics Data Analysis Toolbox™ software includes functions and interactive tools for analyzing and modeling data, learning and teaching statistics.

The Flexible Statistics Data Analysis Toolbox™ supports a set of routines to develop robust and efficient analysis of complex data sets (multivariate, regression, clustering, ...), ensuring an output unaffected by anomalies or deviations from model assumptions.

In addition, it offers a rich set interactive graphical tools which enable us to explore the connection in the various features of the different forward plots.

All Flexible Statistics Data Analysis Toolbox™ functions are written in the open MATLAB® language. This means that you can inspect the algorithms, modify the source code, and create your own custom functions.

For the details about the functions present in FSDA you can browse the categorial and alphabetical list of functions of the toolbox inside MATLAB (once FSDA is installed) or at the web addresses http://rosa.unipr.it/FSDA/function-cate.html and http://rosa.unipr.it/FSDA/function-alpha.html

FSDA

  • Is especially useful in detecting in data potential anomalies (outliers), even when they occur in groups. Can be used to identify sub-groups in heterogeneous data.
  • Extends functionalities in key statistical domains requiring robust analysis (cluster analysis, discriminant analysis, model selection, data transformation).
  • Integrates instruments for interactive data visualization and modern exploratory data analysis, designed to simplify the interpretation of the statistical results by the end user.
  • Provides statisticians, engineers, scientists, financial analysts a comprehensive set of tools to assess and understand their data.
  • Provides practitioners, students and teachers with functions and graphical tools for modeling complex data, learning and teaching statistics.

FSDA is developed for wide applicability. For its capacity to address problems focusing on anomalies in the data, it is expected that it will be used in applications such as anti-fraud, detection of computer network intrusions, e-commerce and credit cards frauds, customer and market segmentation, detection of spurious signals in data acquisition systems, in chemometrics (a wide field covering biochemistry, medicine, biology and chemical engineering), in issues related to the production of official statistics (e.g. imputation and data quality checks), and so on.

For more information see the Wiki page at https://github.com/UniprJRC/FSDA/wiki

Ways to familiarize with the FSDA toolbox

  • Run the examples contained in files examples_regression.m or examples_multivariate.m or examples_categorical.m. Notice that all examples are organized in cells
  • Run the GUIs in the FSDA Matlab help pages. For a preview see http://rosa.unipr.it/FSDA/examples.html

Cite As

Marco Riani (2023). FSDA (https://github.com/UniprJRC/FSDA/releases/tag/8.6.9), GitHub. Retrieved .

MATLAB Release Compatibility
Created with R2022b
Compatible with R2017b to R2022b
Platform Compatibility
Windows macOS Linux

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Version Published Release Notes
8.6.9.0

See release notes for this release on GitHub: https://github.com/UniprJRC/FSDA/releases/tag/8.6.9

8.6.8.0

See release notes for this release on GitHub: https://github.com/UniprJRC/FSDA/releases/tag/8.6.8

8.6.7.0

See release notes for this release on GitHub: https://github.com/UniprJRC/FSDA/releases/tag/8.6.7

8.6.5.0

See release notes for this release on GitHub: https://github.com/UniprJRC/FSDA/releases/tag/8.6.5

8.6.4

See release notes for this release on GitHub: https://github.com/UniprJRC/FSDA/releases/tag/8.6.4

8.6.3

See release notes for this release on GitHub: https://github.com/UniprJRC/FSDA/releases/tag/8.6.3

8.6.2

See release notes for this release on GitHub: https://github.com/UniprJRC/FSDA/releases/tag/8.6.2

8.6.1

See release notes for this release on GitHub: https://github.com/UniprJRC/FSDA/releases/tag/8.6.1

8.6.0

See release notes for this release on GitHub: https://github.com/UniprJRC/FSDA/releases/tag/8.6.0

8.5.38

See release notes for this release on GitHub: https://github.com/UniprJRC/FSDA/releases/tag/8.5.38

8.5.37

See release notes for this release on GitHub: https://github.com/UniprJRC/FSDA/releases/tag/8.5.37

8.5.36

See release notes for this release on GitHub: https://github.com/UniprJRC/FSDA/releases/tag/8.5.36

8.5.35

See release notes for this release on GitHub: https://github.com/UniprJRC/FSDA/releases/tag/8.5.35

8.5.34

See release notes for this release on GitHub: https://github.com/UniprJRC/FSDA/releases/tag/8.5.34

8.5.33

See release notes for this release on GitHub: https://github.com/UniprJRC/FSDA/releases/tag/8.5.33

8.5.31

See release notes for this release on GitHub: https://github.com/UniprJRC/FSDA/releases/tag/8.5.31

8.5.30

See release notes for this release on GitHub: https://github.com/UniprJRC/FSDA/releases/tag/8.5.30

8.5.29

See release notes for this release on GitHub: https://github.com/UniprJRC/FSDA/releases/tag/8.5.29

8.5.28

See release notes for this release on GitHub: https://github.com/UniprJRC/FSDA/releases/tag/8.5.28

8.5.27

See release notes for this release on GitHub: https://github.com/UniprJRC/FSDA/releases/tag/8.5.27

8.5.26

See release notes for this release on GitHub: https://github.com/UniprJRC/FSDA/releases/tag/8.5.26

8.5.25

See release notes for this release on GitHub: https://github.com/UniprJRC/FSDA/releases/tag/8.5.25

8.5.24

See release notes for this release on GitHub: https://github.com/UniprJRC/FSDA/releases/tag/8.5.24

8.5.23

See release notes for this release on GitHub: https://github.com/UniprJRC/FSDA/releases/tag/8.5.23

8.5.22

See release notes for this release on GitHub: https://github.com/UniprJRC/FSDA/releases/tag/8.5.22

8.5.21

See release notes for this release on GitHub: https://github.com/UniprJRC/FSDA/releases/tag/8.5.21

8.5.20

See release notes for this release on GitHub: https://github.com/UniprJRC/FSDA/releases/tag/8.5.20

8.5.19

See release notes for this release on GitHub: https://github.com/UniprJRC/FSDA/releases/tag/8.5.19

8.5.18

See release notes for this release on GitHub: https://github.com/UniprJRC/FSDA/releases/tag/8.5.18

8.5.17

See release notes for this release on GitHub: https://github.com/UniprJRC/FSDA/releases/tag/8.5.17

8.5.16

See release notes for this release on GitHub: https://github.com/UniprJRC/FSDA/releases/tag/8.5.16

8.5.14

New dataset car added to FSDA

8.5.13

New option to add colorbar associated to labels in function CorAnaplot

8.5.12

Improved documentation in the .html associated help files

8.5.11

Improved capabilities in ellipse.m. See
http://rosa.unipr.it/FSDA/ellipse.html

8.5.10

Added version control inside function mdpattern to cope with previous versions of MATLAB

8.5.9

New function mdpattern which finds and plots missing data patterns. For more details see http://rosa.unipr.it/FSDA/mdpattern.html

8.5.8

New options inside LTSts and simulateTS that allow a customized definition of the autoregressive component

8.5.7

New function mcdeda which monitors the output of mcd for a sequence of values of breakdown point

8.5.6

New functions balloonplot (http://rosa.unipr.it/FSDA/balloonplot.html) and moonplot (http://rosa.unipr.it/FSDA/moonplot.html) and new datasets added

8.5.5

New cluster analysis datasets added

8.5.4

FSDA release 2021A fully tested

8.5.3

Added a series of GUIs to show the necessary calculations to obtain of a series of statistical indexes. For more information see for example:
http://rosa.unipr.it/FSDA/GUIregress.html, http://rosa.unipr.it/FSDA/GUIconcentration.html ....

8.5.2

Added new function barVariableWidth which produces a bar plot with different widths and colors for each bar. For a preview see http://rosa.unipr.it/FSDA/barVariableWidth.html.

8.5.1

Added a series of routines for the estimation of integrated and instantaneous variance of a diffusion process via Fourier analysis [Mancino, Recchioni, Sanfelici, ``Fourier-Malliavin Volatility Estimation. Theory and Practice'', 2017, Springer NY

8.5.0

New routines for robust correspondence analysis added

8.4.5

Option commonslope added to tclustreg, tclustregeda and tclustregIC (see for example http://rosa.unipr.it/FSDA/tclustreg.html) . Fixed minor bugs.

8.4.4

New function biplotFS which calls biplotAPP to create the dynamic boxplot (for a preview of the help of this function see http://rosa.unipr.it/FSDA/biplotFS.html). Improvements in function pcaFS (see http://rosa.unipr.it/FSDA/pcaFS.html)

8.4.3

Added option tag in FSR.m in order to tag the plots which are produced.
Now mdrplot.m, mmdplot.m, mdrrsplot.m and mmdrsplot.m have an additional output in order to show the list of brushed units for each brushing operation.

8.4.2

Improvements in functions CorAna and CorAnaplot. New dataset citiesItaly added

8.4.1

New function pcaFS and new app for dynamic biplot (prerelease version)

8.4.0

FSDA 2020b. See release_notes.html for the details of the new version

8.3.4

New function scatterboxplot which creates scatter diagram with marginal boxplots

8.3.3

resubmitted version due to connection problems

8.3.2

Corrected some typos in the documentation

8.3.1

New function waterfallchart.m to create waterfall charts (see https://en.wikipedia.org/wiki/Waterfall_chart). Function funnelplot.m renamed funnelchart.m

8.3.0

New function funnelplot to create funnel charts
https://en.wikipedia.org/wiki/Funnel_chart

8.2.3

Improved javascripts for the HTML help files and minor changes

8.2.2

Corrected minor bug in function tclustregeda

8.2.1

Added new regression clustering datasets. More details in the release_notes.html file

8.2.0

Prerelease 2020b

8.1.1

Updated file readme.md

8.1.0

First release where installation file has been created programmatically.

8.0.3

Typo corrected

8.0.2

New upload due to connection problems

8.0.1

Corrected small bug in file docrootFS

8.0.0

See https://github.com/UniprJRC/FSDA/blob/master/helpfiles/FSDA/release_notes.html for the details or file release_notes.html inside the toolbox

7.5.1

Procedure for copying html help files made easier.

7.5.0

New functions for Power divergence, VIOM model and simulateLM.

7.4.1

Minor typos

7.4

Function LTStsVarSel.m now extends variable selection to AR components. File simulateTS.m does not need anymore the Econometrics toolbox.
New file installHelpFiles.m which automatically enables to copy FSDA html help files into MATLAB docroot

7.3.5

Solved minor bug in function mcd

7.3.4

Logo updated

7.3.3

Logo updated

7.3.2

Logo updated

7.3.1

Logo updated

7.3

Apps images bug solved. Improved version of some html pages.

7.2.0

startup.m removed. Output of the examples of HTML files now available for downloading. More details in getting_started.mlx page.

7.1.3

HTML pointers files inside (FSDAroot)/helpfiles/pointersHTML regenerated.
Corrected bug in function existFS.

7.1.2.3

License files updated

7.1.2.2

Function rescale renamed rescaledFS because in conflict with function rescale of MATLAB. FSDA dataset hospital renamed hospitalFS because it shadowed MATLAB dataset hospital. Thank you for the suggestions.

7.1.2.1

Typo fixed

7.1.2

Deleted space in the installation folder

7.1.1

Improved file GettingStarted.mlx

7.1

To view or report issues in this GitHub add-on, visit the GitHub Repository.
To view or report issues in this GitHub add-on, visit the GitHub Repository.