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FSDA

version 8.5.4 (15.6 MB) by Marco Riani
Robust regression, robust multivariate analysis, robust classification and much more...

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Updated 29 Mar 2021

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FSDA Toolbox contains more than 300 routines to assess and understand data affected by multiple outliers. FSDA routines cover, multiple regression, multivariate data analysis, classification and transformations. FSDA also includes interactive tools for analyzing and modeling data, learning and teaching statistics. Every .m function has its corresponding HTML page in Mathworks style (which is generated automatically). The documentation system is perfectly integrated into the Mathworks framework.

Cite As

Marco Riani (2021). FSDA (https://www.mathworks.com/matlabcentral/fileexchange/72999-fsda), MATLAB Central File Exchange. Retrieved .

Comments and Ratings (111)

Enrico Moretto

Very well done!

Beatrice ORZI

Martina GIARDINA

Martina MASERA

Silvia Bonini

Naman CHANDRAYAN

Advanced

Ilma HUNDA

Lorenzo PARADISI

Michele CAMPIDELLI

bing lub

great I just need it

Yun Xu

junhan park

Chiara Pagliari

Alessandro STIFANI

Arianna MISOLIC

Sara COLETTI

Francesca CAVAIOLA

GIHANE KETRI

Fabrizio Laurini

Alessandra MILAZZO

Davide GABRIELLI

Sara TARQUINIO

Alessandro Bragazzi

Very useful

Cecilia CASTAGNA

Virginia PISU

A very useful feature.

Mattia Guaraldi

Alessandro CORRADI

Rei ALUSHAJ

Gaia La Torre

Carla MANZONI

Tommaso PAGLIAI

Nicola TASSONI

Manfredi PENNISI

Samantha SCIORTINO

Nabil BOUCHNAK

Sofia COVOLO

Supraja KUMAR

Mariavittoria MIGNOLI

Fabio DE LUCA

Valentina TARASCONI

Alessia MONTANARI

Leonardo CALZATI

Andrea Spaggiari

Elisa TREGLIA

Alberto RIVELLINO

Vittorio Zanni

Matilde SPINA

Miriana NACCI

Giovanni ALLODI

Michael OLIVIERO

Carlotta DANNA

Great!

Francesca GARGIULO

Chiara Pedretti

Alessia ALBERTI

Irene TOSI

Micaela BROCCHINI

Cristina LOVAGLIO

Marta Micol CAPURSO

Sara DEFIORI

Althea Mora

Francesco COTUGNO

Michael Garsi

Excellent tool to evaluate and understand the data being analyzed.

Martina Carnazza

Riccardo ROSA

it's great

Miriam Tatta

Leonardo IANIA

Valentina FUSI

Isabella CARBONE

Extrimely useful, especially for analysing data for marketing. Thank you!

Lucia TANZI

Giulia CASAZZA

Great!

Sara DEFIORI

Sara DEFIORI

Marie Anna NOVIELLO

Alessio CORTESE

Costanza CAPELLI

Sonia VIRDI

Paola HOXHA

Virginia NIEPPI

Riccardo SETTI

Diego MONTALI

Valerio MAURIZIO

Mirko ANCESCHI

Giammarco FERRANTE

Aldo Corbellini

Dear Jonas, we thank you for your suggestions. In version 8.4.3 of FSDA we made the modifications you suggested. More precisely:
1. We have added option tag in FSR.m in order to tag the plots, which are produced. For a preview of the documentation see link: http://rosa.unipr.it/FSDA/FSR.html#input_argument_namevalue_tag

2. 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, see for example this link: http://rosa.unipr.it/fsda/mdrrsplot.html#ExtraExample_7

Jonas

In FSRcore.m one could possibly add the "Tag" to the figure, so that we are able to modify the plots later on. Also, it would be nice to obtain the indices of the "brushed" data points as well as the "brushing group" in mdrplot.m. Currently, I modify several functions, just to get a feedback. Thus, any update will cause some troubles.
However, beside from this minor issues: GREAT JOB, thank you!

Luca Poggianti

Mirko Anello

Teodo

Daniele G

Domenico Perrotta

Good idea to add use-cases. Thanks Mohammed. This will require some time, but in the meantime you can find an important usecase at this link: https://ec.europa.eu/jrc/en/publication/robust-estimation-monthly-prices-goods-traded-european-union. Everything you see there is based on FSDA functions.

Marco Riani

For a short intro please see the related GitHub web site
https://uniprjrc.github.io/FSDA/
or the video https://www.youtube.com/watch?v=VyPyoecUdQU

Mohammad Rahmani

Wonderful! Please add a short into/usecase pdf

Silvia Salini

I like FSDA!

Agustín Iscar

Luigi Grossi

carmelo ludovico

Giorgio Gozzi

Fabrizio Laurini

Great stuff!

Michele Donati

Alberto BERNARDI

Paolo POLLONARA

Giovanni VERGA

Cecilia RIANI

Gian23

Luca Insolia

heyla hugorson

Aldo Corbellini

MATLAB Release Compatibility
Created with R2021a
Compatible with R2015b and later releases
Platform Compatibility
Windows macOS Linux

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