Multivariate Inference

by Alvin C. Rencher

Book Overview

Multivariate analysis seeks to discover or test patterns in data. It is used to gain information despite a multiplicity of variables. Multivariate descriptive techniques enable scientists to look beneath the surface of a statistical system and extract its essence.

• Format: Hardcover
• Language: English
• ISBN: 0471571512
• ISBN13: 9780471571513
• Release Date: December 1997
• Publisher: Wiley-Interscience
• Length: 592 Pages
• Weight: 2.23 lbs.
• Dimensions: 1.5" x 6.4" x 9.6"

Customer Reviews

nice modern treatment

Rencher covers the basics of multivariate analysis based on multivariate normal theory. It is a graduate text in statistics much like the classic of Ted Anderson. It covers Hotelling's T square, the multivariate analysis of variance, discriminant analysis and classification, multivariate regression, canonical correlation, principal components and factor analysis. In addition to the standard stuff he also discusses robust methods and introduces the bootstrap. The chapter on classification includes coverage of bootstrap bias adjustment in error rate estimation and includes discussion of some of the simulation work in this area including some of my papers with Murthy and Nealy. This book contains a very useful and up-to-date bibliography