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Multiple Factor Analysis by Example Using R

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''An introduction to exploratory techniques for multivariate data analysis, this book covers the key methodology, including principal components analysis, correspondence analysis, mixed models and multiple factor analysis. The authors take a practical approach, with examples leading the discussion of the methods and lots of graphics to emphasize visualization. They present the concepts in the most intuitive way Read more...

Author(s): François Husson; Sébastien Lê; Jérôme Pagès
Series: Chapman & Hall/CRC The R Series
Publisher: CRC Press
Year: 2014

Language: English
Pages: xii, 228 pages : ill ; 25 cm
City: Boca Raton
Tags: Библиотека;Компьютерная литература;R;


Content: Principal component analysis (PCA) --
Correspondence analysis (CA) --
Multiple correspondence analysis (MCA) --
Clustering.
Abstract: ''An introduction to exploratory techniques for multivariate data analysis, this book covers the key methodology, including principal components analysis, correspondence analysis, mixed models and multiple factor analysis. The authors take a practical approach, with examples leading the discussion of the methods and lots of graphics to emphasize visualization. They present the concepts in the most intuitive way possible, keeping mathematical content to a minimum or relegating it to the appendices. The book includes examples that use real data from a range of scientific disciplines and implemented using an R package developed by the authors''