Canonical correlation analysis: an introduction to a multivariate statistical analysis

Generalization of Canonical Correlation Analysis from Multivariate to Functional Cases and its related problems

In multivariate cases, the aim of canonical correlation analysis (CCA) for two sets of variables x and y is to obtain linear combinations of them so that they have the largest possible correlation. However, when x and y are continouse functions of another variable (generally time) in nature, these two functions belong to function spaces which are of infinite dimension, and CCA for them should b...

Introduction to Multivariate Statistical Analysis in Chemometrics

Why to read "yet another book" on statistical methods? This is a question that may arise among chemometricians, chemists, students or anyone using chemometric methods in their research or everyday routine work. However, this book is a very good contribution to a better understanding of statistics because it really captures the point of potential misunderstanding between chemists and mathematici...

Multivariate statistical analysis: a brief introduction.

* Associate Professor Department of Community, Occupational and Family Medicine National University of Singapore Address for Reprints: Dr Chia Kee Seng, Department of Community, Occupational and Family Medicine, National University of Singapore, Lower Kent Ridge Road, Singapore 119260. Introduction In modern medical research, it is rare to limit data analysis to merely two variables: a single e...

Statistical Consistency of Kernel Canonical Correlation Analysis

While kernel canonical correlation analysis (CCA) has been applied in many contexts, the convergence of finite sample estimates of the associated functions to their population counterparts has not yet been established. This paper gives a mathematical proof of the statistical convergence of kernel CCA, providing a theoretical justification for the method. The proof uses covariance operators defi...

An Introduction to Applied Multivariate Analysis