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Multiparametric Statistics.

This book presents the latest mathematical investigations used to solve a new class of statistical problem characterized by high complexity along with shortage of data. For these problems, traditional methods of multivariate statistics used in hundreds of software packages prove to be inefficient, u...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Serdobolskii, Vadim Ivanovich
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Burlington : Elsevier, 2007.
Temas:
Acceso en línea:Texto completo

MARC

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505 0 |a Front Cover; Multiparametric Statistics; Copyright Page; On the Author; Table of Contents; Foreword; Preface; Chapter 1. Introduction; Chapter 2. Fundamental Problem of Statistics; Chapter 3. Spectral Theory of Sample Covariance Matrices; Chapter 4. Asymptotically Unimprovable Solution of Multivariate Problems; Chapter 5. Multiparametric Discriminant Analysis; Chapter 6. Theory of Solution to High-Order Systems of Empirical Linear Algebraic Equations; Appendix: Experimental Investigation of Spectral Functions of Large Sample Covariance Matrices; References; Index. 
520 |a This book presents the latest mathematical investigations used to solve a new class of statistical problem characterized by high complexity along with shortage of data. For these problems, traditional methods of multivariate statistics used in hundreds of software packages prove to be inefficient, unstable and often do not work at all. This monograph, for the first time in the history of mathematical statistics, brings a fruitful approach for the systematic construction of efficient nearly exact statistical procedures. 
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