Correspondence Analysis and Data Coding with Java and R: 1st Edition (Hardback) book cover

Correspondence Analysis and Data Coding with Java and R

1st Edition

By Fionn Murtagh

Chapman and Hall/CRC

256 pages | 56 B/W Illus.

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pub: 2005-05-26
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Developed by Jean-Paul Benzérci more than 30 years ago, correspondence analysis as a framework for analyzing data quickly found widespread popularity in Europe. The topicality and importance of correspondence analysis continue, and with the tremendous computing power now available and new fields of application emerging, its significance is greater than ever.

Correspondence Analysis and Data Coding with Java and R clearly demonstrates why this technique remains important and in the eyes of many, unsurpassed as an analysis framework. After presenting some historical background, the author presents a theoretical overview of the mathematics and underlying algorithms of correspondence analysis and hierarchical clustering. The focus then shifts to data coding, with a survey of the widely varied possibilities correspondence analysis offers and introduction of the Java software for correspondence analysis, clustering, and interpretation tools. A chapter of case studies follows, wherein the author explores applications to areas such as shape analysis and time-evolving data. The final chapter reviews the wealth of studies on textual content as well as textual form, carried out by Benzécri and his research lab. These discussions show the importance of correspondence analysis to artificial intelligence as well as to stylometry and other fields.

This book not only shows why correspondence analysis is important, but with a clear presentation replete with advice and guidance, also shows how to put this technique into practice. Downloadable software and data sets allow quick, hands-on exploration of innovative correspondence analysis applications.


"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

Table of Contents


Data Analysis

Notes on the History of Data Analysis

Correspondence Analysis or Principal Components Analysis

R Software for Correspondence Analysis and Clustering


Vectors and Projections



Algebraic Perspective



Further R Software for Correspondence Analysis




From Doubling to Fuzzy Coding and Beyond

Assessment of Coding Methods

The Personal Equation and Double Rescaling

Case Study: DNA Exon and Intron Junction Discrimination

Conclusions on Coding

Java Software


Introduction to Analysis of Size and Shape

Comparison of Prehistoric and Modern Groups of Canids

Craniometric Data from Ancient Egyptian Tombs

Time-Varying Data Analysis: Examples from Economics

Financial Modeling and Forecasting



Correspondence Analysis

Tool Words: Between Analysis of Form and Analysis of Content Towards Content Analysis

Textual and Documentary Typology

Conclusion: Methodology in Free Text Analysis

Software for Text Processing

Introduction to the Text Analysis Case Studies

Eight Hypotheses of Parmenides Regarding the One

Comparative Study of Reality, Fable and Dream

Single Document Analysis

Conclusion on Text Analysis Case Studies

Concluding Remarks



About the Originator

About the Series

Chapman & Hall/CRC Computer Science & Data Analysis

Learn more…

Subject Categories

BISAC Subject Codes/Headings:
MATHEMATICS / Probability & Statistics / General