Exploratory multivariate analysis by example using R /

By:

Husson, François

Contributor(s):

Material type: Text

TextSeries: Chapman & Hall/CRC computer science and data analysisPublication details: Boca Raton : CRC Press, c2011.Description: xii, 228 pISBN:

9781439835807 (hardback)

Subject(s):

DDC classification:

519.5'350285 HUS

LOC classification:

QA278 .H87 2011

Summary: 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.

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Previous	519.5'35 AFI Practical multivariate analysis /	519.5'35 HAR Multivariate statistics :	519.5'35 MAR Exploratory data analysis with MATLAB /	519.5'350285 HUS Exploratory multivariate analysis by example using R /	519.5'5 KIT Introduction to time series modeling /	519.5'5 PRA Time series :	519.2 POL Introduction to statistical limit theory /	Next

A Chapman & Hall book.

Includes bibliographical references and index.

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.

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