【统计理论与方法，R 书籍】 Correspondence Analysis in Practice (2016, 3e)

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Correspondence Analysis in Practice, Third Edition

Michael Greenacre



Drawing on the author’s 45 years of experience in multivariate analysis, Correspondence Analysis in Practice, Third Edition, shows how the versatile method of correspondence analysis (CA) can be used for data visualization in a wide variety of situations. CA and its variants, subset CA, multiple CA and joint CA, translate two-way and multi-way tables into more readable graphical forms — ideal for applications in the social, environmental and health sciences, as well as marketing, economics, linguistics, archaeology, and more.

Features

• Completely revised, up-to-date edition that continues with the unique didactic format of the second edition, each chapter having a fixed eight pages of study material, with extensive marginal notes, informative figure and table captions, and end-of chapter summaries

• Five new chapters on correspondence analysis of networks, compositional data analysis, analysis of matched matrices, co-inertia & co-correspondence analysis, and permutation tests

• Nontechnical presentation of CA, gathering the mathematical aspects in a compact theoretical appendix

• Numerous examples and case studies from the social and environmental sciences

• Computational appendix that documents the ca package for R developed by the author and summarizes the R commands for many analyses in the book, making it easy for readers to reproduce the results

Table of Contents

Preface

Scatterplots and Maps

Profiles and the Profile Space

Masses and Centroids

Chi-Square Distance and Inertia

Plotting Chi-Square Distances

Reduction of Dimensionality

Optimal Scaling

Symmetry of Row and Column Analyses

Two-Dimensional Maps

Three More Examples

Contributions to Inertia

Supplementary Points

Correspondence Analysis Biplots

Transition and Regression Relationships

Clustering Rows and Columns

Multiway Tables

Stacked Tables

Multiple Correspondence Analysis

Joint Correspondence Analysis

Scaling Properties of MCA

Subset Correspondence Analysis

Analysis of Matches Matrices

Analysis of Square Tables

Correspondence Analysis of Networks

Data Recoding

Canonical Correspondence Analysis

Co-Inertia and Co-Correspondence Analysis

Aspects of Stability and Inference

Permutation Tests

Appendix A: Theory of Correspondence Analysis

Appendix B: Computation of Correspondence Analysis

Appendix C: Bibliography of Correspondence Analysis

Appendix D: Glossary of Terms

Appendix E: Epilogue

Index

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