The book presents important tools and techniques for treating problems in m- ern multivariate statistics in a systematic way. The ambition is to indicate new directions as well as to present the classical part of multivariate statistical analysis in this framework. The book has been written for graduate students and statis- cians who are not afraid of matrix formalism. The goal is to provide them with a powerful toolkit for their research and to give necessary background and deeper knowledge for further studies in di?erent areas of multivariate statistics. It can also be useful for researchers in applied mathematics and for people working on data analysis and data mining who can ?nd useful methods and ideas for solving their problems. Ithasbeendesignedasatextbookforatwosemestergraduatecourseonmultiva- ate statistics. Such a course has been held at the Swedish Agricultural University in 2001/02. On the other hand, it can be used as material for series of shorter courses. In fact, Chapters 1 and 2 have been used for a graduate course Matrices in Statistics at University of Tartu for the last few years, and Chapters 2 and 3 formed the material for the graduate course Multivariate Asymptotic Statistics in spring 2002. An advanced course Multivariate Linear Models may be based on Chapter 4. A lot of literature is available on multivariate statistical analysis written for di?- ent purposes and for people with di?erent interests, background and knowledge.

Comprehensive presentation of matrix algebra useful for statistics Advanced presentation of the normal, Wishart and the elliptical distributions A unified approach to multivariate density approximations An up-to-date treatment of multivariate linear normal models Throughout, for each topic, many unpublished results and derivations are given

Inhalt
Basic Matrix Theory and Linear Algebra.- Multivariate Distributions.- Distribution Expansions.- Multivariate Linear Models.