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Multivariate Data Analysis on Matrix Manifolds

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Cover of 'Multivariate Data Analysis on Matrix Manifolds'

Table of Contents

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    Book Overview
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    Chapter 1 Introduction
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    Chapter 2 Matrix analysis and differentiation
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    Chapter 3 Matrix manifolds in MDA
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    Chapter 4 Principal component analysis (PCA)
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    Chapter 5 Factor analysis (FA)
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    Chapter 6 Procrustes analysis (PA)
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    Chapter 7 Linear discriminant analysis (LDA)
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    Chapter 8 Cannonical correlation analysis (CCA)
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    Chapter 9 Common principal components (CPC)
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    Chapter 10 Metric multidimensional scaling (MDS) and related methods
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    Chapter 11 Data analysis on simplexes
Attention for Chapter 6: Procrustes analysis (PA)
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