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＜電子ブック＞
Advanced Multivariate Statistics with Matrices / by Tõnu Kollo, D. von Rosen
(Mathematics and Its Applications ; 579)

版	1st ed. 2005.
出版者	(Dordrecht : Springer Netherlands : Imprint: Springer)
出版年	2005
本文言語	英語
大きさ	XVI, 490 p : online resource
著者標目	*Kollo, Tõnu author Rosen, D. von author SpringerLink (Online service)
件　名	LCSH:Statistics  LCSH:Algebras, Linear LCSH:Approximation theory FREE:Statistical Theory and Methods FREE:Linear Algebra FREE:Approximations and Expansions
一般注記	Basic Matrix Theory and Linear Algebra -- Multivariate Distributions -- Distribution Expansions -- Multivariate Linear Models 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 HTTP:URL=https://doi.org/10.1007/1-4020-3419-9

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