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Correspondence Analysis and Data Coding with Java and R

Fionn Murtagh

$315

Hardback

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English
Chapman & Hall/CRC
26 May 2005
Correspondence analysis is a descriptive/exploratory statistical technique designed to analyze simple two-way and multi-way tables containing a measure of correspondence between rows and columns. The results allow analysts to explore categorical variables. This book provides an introduction to the theory and applications of correspondence analysis, with an emphasis on data coding -- the first step in correspondence analysis. It features a practical presentation of the theory with a range of applications from data mining, financial engineering, and the biosciences. Implementation of the methods is presented using JAVA and R(S-Plus) software. The author also provides Web support for readers.

By:  
Imprint:   Chapman & Hall/CRC
Country of Publication:   United States
Volume:   5
Dimensions:   Height: 234mm,  Width: 156mm,  Spine: 19mm
Weight:   498g
ISBN:   9781584885283
ISBN 10:   1584885289
Series:   Chapman & Hall/CRC Computer Science & Data Analysis
Pages:   256
Publication Date:  
Audience:   Professional and scholarly ,  Professional and scholarly ,  Professional & Vocational ,  Undergraduate ,  Further / Higher Education
Format:   Hardback
Publisher's Status:   Active

Murtagh, Fionn

Reviews for Correspondence Analysis and Data Coding with Java and R

"""Detailed examples of its application to data are drawn from an astonishingly wide variety of fields; astronomy, financial modeling and forecasting, comparisons of prehistoric and modern groups of dogs, ancient goblets and measurements on ancient Egyptian skulls. …All in all this book can be recommended as a succinct reference on all aspects of correspondence analysis, theoretical, computational, and practical."" -J.M. Juritz, Short Book Reviews of the ISI ""This book plays an important role in bridging the gap between learning a method and actually implementing it . . . could serve as either a text for an introductory course on CA or as a supplementary text to a more advanced graduate course in CA or multivariate techniques in general . . . The author should be commended for bringing these issues to the forefront."" – Douglas Steinley, University of Missouri-Columbia, in Psychometrika, March 2007, Vol. 74, No. 1"


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