Principal Component and Correspondence Analyses Using R

Name: Principal Component and Correspondence Analyses Using R
Brand: Springer International Publishing AG
SKU: 9783319092553
Price: 1082 CZK
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Autor: Hervé Abdi, Derek Beaton

Jazyk:

Vazba: Brožovaná

Vydavatel: Springer International Publishing AG

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With the right R packages, R is uniquely suited to perform Principal Component Analysis (PCA), Corre...

Informace o knize

Autor

Hervé Abdi, Derek Beaton

Jazyk

Angličtina

Vazba

Kniha - Brožovaná

Vydáno

2022

Stránek

110

EAN

9783319092553

ISBN

3319092553

Enbook ID

02782978

Vydavatel

Springer International Publishing AG

Rozměry

155 x 235

Kompletní popis

With the right R packages, R is uniquely suited to perform Principal Component Analysis (PCA), Correspondence Analysis (CA), Multiple Correspondence Analysis (MCA), and metric multidimensional scaling (MMDS). The analyses depicted in this book use several packages specially developed for theses analyses and include (among others): the ExPosition suite, FactoMiner , ade4, and ca. The authors present each technique with one or several small examples that demonstrate how to enter the data, perform the standard analyses, and obtain professional quality graphics. Through explanations of the major options for how to carry out each method, readers can tailor the content of this book to their particular goals. Explanations include the effects of using particular packages. ExPosition is a great choice for the methods as it was written specifically for this book. However, options abound and are illustrated within unique scenarios. The first chapter includes installation of the packages. At the end of the book, a short appendix presents critical mathematical material for readers who want to go deeper into the theory.§

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Principal Component and Correspondence Analyses Using R

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