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Contents
Front Matter
Introduction
1.
Chapter 1
2.
Introduction to Multivariate Analysis
3.
Multivariate Normal Distribution and Related Inference: I
4.
Multivariate Normal Distribution and Related Inference: II
5.
Multivariate Normal Distribution and Related Inference: V
6.
Multivariate Normal Distribution and Related Inference: VI
7.
Multivariate Analysis of Variance
8.
Multivariate Linear Models - I
9.
Multivariate Linear Models: II
10.
Multivariate Linear Models: III
11.
Multivariate Linear Models: IV
12.
Multivariate Linear Models: V
13.
Multivariate Linear Models: VI
14.
Hotelling T2 Test and MANOVA using R
15.
Introduction to Principal Components Analysis
16.
Principal Components Analysis -Related Results
17.
Principal Components Analysis -Further Results
18.
Sample Principal Components
19.
Principal Component Analysis using R
20.
Factor Analysis : Estimation Techniques 1
21.
Factor Analysis : Estimation Techniques 2
22.
Finding Factor Scores
23.
Factor Analysis using R
24.
Canonical Correlation
25.
More on Canonical Correlations
26.
Clustering Techniques - The Partitioning Methods
27.
Discriminant Analysis and Classication
28.
Classification for Normal Populations
29.
Classifications with Several Variables (References)
30.
Fisher's Discriminant Function
Back Matter
Appendix
Multivariate analysis
26
Clustering Techniques – The Partitioning Methods
Souvik Bandyopadhyay
you can view video on Clustering Techniques – The Partitioning Methods
