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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.
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.
The book aims to present a wide range of the newest results on
multivariate statistical models, distribution theory and
applications of multivariate statistical methods. A paper on
Pearson-Kotz-Dirichlet distributions by Professor N Balakrishnan
contains main results of the Samuel Kotz Memorial Lecture.
Extensions of linear models to multivariate exponential dispersion
models and Growth Curve models are presented, and several papers on
classification methods are included. Applications range from
insurance mathematics to medical and industrial statistics and
sampling algorithms.
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