Correspondence Analysis and Data Coding with Java and R

Correspondence Analysis and Data Coding with Java and R

by Fionn Murtagh, Murtagh Murtagh, Fionn Murtaugh
     
 

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.

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Overview

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.

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Product Details

ISBN-13:
9781584885283
Publisher:
Taylor & Francis
Publication date:
06/10/2005
Series:
Chapman & Hall/CRC Computer Science & Data Analysis Series, #6
Edition description:
New Edition
Pages:
256
Product dimensions:
6.30(w) x 9.30(h) x 0.70(d)

Table of Contents

INTRODUCTION
Data Analysis
Notes on the History of Data Analysis
Correspondence Analysis or Principal Components Analysis
R Software for Correspondence Analysis and Clustering

THEORY OF CORRESPONDENCE ANALYSIS
Vectors and Projections
Factors
Transform
Algebraic Perspective
Clustering
Questions
Further R Software for Correspondence Analysis
Summary

INPUT DATA CODING
Introduction
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

EXAMPLES AND CASE STUDIES
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

CONTENT ANALYSIS OF TEXT
Introduction
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

References
Index

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