02196cam a2200373Ia 4500 CRC0KE11623PDF BD-DhSAU 20151012144306.0 m|||||o||d|||||||| cr|||| 110310s2011 fluad sb 001 0 eng d 9781439835814 (ebook : PDF) BD-DhSAU BD-DhSAU QA278 .H87 2011 519.53502855133 H972 Husson, Fran�cois. Exploratory multivariate analysis by example using R [electronic resource] / Fran�cois Husson, S�ebastien L�e, J�er�ome Pag�es. Boca Raton : CRC Press, 2011. xii, 228 p. : ill. Chapman & Hall/CRC computer science & data analysis Includes bibliographical references and index. 1. Principal component analysis (PCA) -- 2. Correspondence analysis (CA) -- 3. Multiple correspondence analysis (MCA) -- 4. Clustering. "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"-- Provided by publisher. Also available in print edition. Mode of access: World Wide Web. Multivariate analysis. R (Computer program language) Electronic books. lcsh L�e, S�ebastien. Pag�es, J�er�ome. 9781439835807 Series in computer science and data analysis. http://marc.crcnetbase.com/isbn/9781439835814 application/PDF 11774 11773