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|a 1322635528
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|a 1482205483
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|a 9780429171086
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|a 1498786693
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|a 9781498786690
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|a QA276.45.R3
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|a Pagès, Jérôme
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|a Multiple factor analysis by example using R
|c Jérôme Pagès
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|a Boca Raton
|b CRC Press
|c 2015
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| 300 |
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|a 1 online resource
|b illustrations
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|a 1. Principal component analysis -- 2. Multiple correspondence analysis -- 3. Factorial analysis of mixed data -- 4. Weighting groups of variables -- 5. Comparing clouds of partial individuals -- 6. Factors common to different groups of variables -- 7. Comparing groups variables and Indscal model -- 8. Qualitative and mixed data -- 9. Multiple factor analysis and Procrustes analysis -- 10. Hierarchial multiple factor analysis -- 11. Matrix calculus and Euclidean vector space
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|a Includes bibliographical references
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| 653 |
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|a R (logiciel) / ram
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|a MATHEMATICS / Applied / bisacsh
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| 653 |
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|a Factor Analysis, Statistical
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| 653 |
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|a MATHEMATICS / Probability & Statistics / General / bisacsh
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| 653 |
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|a Analyse factorielle / ram
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| 653 |
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|a Analyse factorielle
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| 653 |
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|a Factor analysis / fast
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| 653 |
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|a R (Computer program language) / Statistical methods
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| 653 |
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|a Factor analysis / http://id.loc.gov/authorities/subjects/sh85046817
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| 653 |
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|a R (Langage de programmation) / Méthodes statistiques
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|a eng
|2 ISO 639-2
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| 989 |
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|b OREILLY
|a O'Reilly
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|a Chapman & Hall/CRC the R series
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|a 10.1201/b17700
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|u https://learning.oreilly.com/library/view/~/9781498786690/?ar
|x Verlag
|3 Volltext
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|a 510
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|a 519.50285536
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|a 519.5
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|a Multiple factor analysis (MFA) enables users to analyze tables of individuals and variables in which the variables are structured into quantitative, qualitative, or mixed groups. Written by the co-developer of this methodology, Multiple Factor Analysis by Example Using R brings together the theoretical and methodological aspects of MFA. It also includes examples of applications and details of how to implement MFA using an R package (FactoMineR). The first two chapters cover the basic factorial analysis methods of principal component analysis (PCA) and multiple correspondence analysis (MCA). The
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