Book description
Multiple factor analysis (MFA) enables users to analyze tables of individuals and variables in which the variables are structured into quantitative, qualitative, or mixed groups. Written by the codeveloper of the methodology, this book brings together the theoretical and methodological aspects of MFA. It also covers principal component analysis, multiple correspondence analysis, factor analysis for mixed data, hierarchical MFA, and more. The book also includes examples of applications and details on how to implement MFA using an R package, with the data and R scripts available online.
Table of contents
 Preliminaries
 Preface

Chapter 1 Principal Component Analysis
 1.1 Data, Notations
 1.2 Why Analyse a Table with PCA?
 1.3 Clouds of Individuals and Variables
 1.4 Centring and Reducing
 1.5 Fitting Clouds NI and NK
 1.6 Interpretation Aids
 1.7 First Example: 909 Baccalaureate Candidates
 1.8 Supplementary Elements
 1.9 Qualitative Variables in PCA
 1.10 Second Example: Six Orange Juices
 1.11 PCA in FactoMineR
 Chapter 2 Multiple Correspondence Analysis
 Chapter 3 Factorial Analysis of Mixed Data
 Chapter 4 Weighting Groups of Variables
 Chapter 5 Comparing Clouds of Partial Individuals
 Chapter 6 Factors Common to Different Groups of Variables
 Chapter 7 Comparing Groups of Variables and Indscal Model

Chapter 8 Qualitative and Mixed Data
 8.1 Weighted MCA
 8.2 MFA of Qualitative Variables
 8.3 Mixed Data
 8.4 Application (Biometry2)
 8.5 MFA of Mixed Data in FactoMineR

Chapter 9 Multiple Factor Analysis and Procrustes Analysis
 9.1 Procrustes Analysis

9.2 Comparing MFA and GPA
 9.2.1 Representing NjI
 9.2.2 Mean Cloud
 9.2.3 Objective, Criterion, Algorithm
 9.2.4 Properties of the Representations of NjI
 9.2.5 A First Appraisal
 9.2.6 Harmonising the Inertia of NjI
 9.2.7 Relationships Between Homologous Factors
 9.2.8 Representing Individuals
 9.2.9 Interpretation Aids
 9.2.10 Representing the Variables
 9.3 Application (Data 23−1)
 9.4 Application to the Ten Touraine Wines
 9.5 Conclusion
 9.6 GPA in FactoMineR
 Chapter 10 Hierarchical Multiple Factor Analysis
 Chapter 11 Matrix Calculus and Euclidean Vector Space
 Bibliography
Product information
 Title: Multiple Factor Analysis by Example Using R
 Author(s):
 Release date: November 2014
 Publisher(s): Chapman and Hall/CRC
 ISBN: 9781498786690
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