Theory of Multivariate Statistics

Author:   Martin Bilodeau ,  David Brenner
Publisher:   Springer-Verlag New York Inc.
Edition:   Softcover reprint of the original 1st ed. 1999
ISBN:  

9781475773033


Pages:   290
Publication Date:   06 May 2013
Format:   Paperback
Availability:   Manufactured on demand   Availability explained
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Theory of Multivariate Statistics


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Overview

Our object in writing this book is to present the main results of the modern theory of multivariate statistics to an audience of advanced students who would appreciate a concise and mathematically rigorous treatment of that material. It is intended for use as a textbook by students taking a first graduate course in the subject, as well as for the general reference of interested research workers who will find, in a readable form, developments from recently published work on certain broad topics not otherwise easily accessible, as for instance robust inference (using adjusted likelihood ratio tests) and the use of the bootstrap in a multivariate setting. A minimum background expected of the reader would include at least two courses in mathematical statistics, and certainly some exposure to the calculus of several variables together with the descriptive geometry of linear algebra.

Full Product Details

Author:   Martin Bilodeau ,  David Brenner
Publisher:   Springer-Verlag New York Inc.
Imprint:   Springer-Verlag New York Inc.
Edition:   Softcover reprint of the original 1st ed. 1999
Dimensions:   Width: 15.50cm , Height: 1.70cm , Length: 23.50cm
Weight:   0.480kg
ISBN:  

9781475773033


ISBN 10:   147577303
Pages:   290
Publication Date:   06 May 2013
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

Table of Contents

Linear algebra.- Random vectors.- Gamma, Dirichlet, and F distributions.- Invariance.- Multivariate normal.- Multivariate sampling.- Wishart distributions.- Tests on mean and variance.- Multivariate regression.- Principal components.- Canonical correlations.- Asymptotic expansions.- Robustness.- Bootstrap confidence regions and tests.

Reviews

This is an excellent graduate level textbook with several challenging problems in the exercises. An outstanding feature of the book is the presentation style. The authors' presentations of core statistical ideas, important formulae, the scope and the limitations of the topics create a curiosity to continue reading. ... I enjoyed reading this book and learned a lot! Short Book Reviews, Vol. 20/2, August 2000


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