Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book enables readers who may not be familiar with matrices to understand a variety of multivariate analysis procedures in matrix forms. Another feature of the book is that it emphasizes what model underlies a procedure and what objective function is optimized for fitting the model to data. The author believes that the matrix-based learning of such models and objective functions is the fastest way to comprehend multivariate data analysis. The text is arranged so that readers can intuitively capture the purposes for which multivariate analysis procedures are utilized: plain explanations of the purposes with numerical examples precede mathematical descriptions in almost every chapter.This volume is appropriate for undergraduate students who already have studied introductory statistics. Graduate students and researchers who are not familiar with matrix-intensive formulations of multivariate data analysis will also find the book useful, as it is based on modern matrix formulations with a special emphasis on singular value decomposition among theorems in matrix algebra.The book begins with an explanation of fundamental matrix operations and the matrix expressions of elementary statistics, followed by the introduction of popular multivariate procedures with advancing levels of matrix algebra chapter by chapter. This organization of the book allows readers without knowledge of matrices to deepen their understanding of multivariate data analysis. 316 pp. Englisch. N� de r�f. du vendeur 9789811095955

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Matrix-Based Introduction to Multivariate Data Analysis

Adachi, Kohei

Edit� par Springer, 2018

ISBN 10 : 9811095957 ISBN 13 : 9789811095955

Neuf Couverture souple

Vendeur : Books Puddle, New York, NY, Etats-Unis

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Etat : New. pp. 301. N� de r�f. du vendeur 26382273013

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Matrix-Based Introduction to Multivariate Data Analysis

Kohei Adachi

Edit� par Springer Nature Singapore, Springer Nature Singapore, 2018

ISBN 10 : 9811095957 ISBN 13 : 9789811095955

Neuf Taschenbuch

Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne

�valuation du vendeur 5 sur 5 �toiles

Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - This book enables readers who may not be familiar with matrices to understand a variety of multivariate analysis procedures in matrix forms. Another feature of the book is that it emphasizes what model underlies a procedure and what objective function is optimized for fitting the model to data. The author believes that the matrix-based learning of such models and objective functions is the fastest way to comprehend multivariate data analysis. The text is arranged so that readers can intuitively capture the purposes for which multivariate analysis procedures are utilized: plain explanations of the purposes with numerical examples precede mathematical descriptions in almost every chapter.This volume is appropriate for undergraduate students who already have studied introductory statistics. Graduate students and researchers who are not familiar with matrix-intensive formulations of multivariate data analysis will also find the book useful, as it is based on modern matrix formulations with a special emphasis on singular value decomposition among theorems in matrix algebra.The book begins with an explanation of fundamental matrix operations and the matrix expressions of elementary statistics, followed by the introduction of popular multivariate procedures with advancing levels of matrix algebra chapter by chapter. This organization of the book allows readers without knowledge of matrices to deepen their understanding of multivariate data analysis. N� de r�f. du vendeur 9789811095955

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Matrix-Based Introduction to Multivariate Data Analysis

Kohei Adachi

Edit� par Springer Singapore, 2018

ISBN 10 : 9811095957 ISBN 13 : 9789811095955

Neuf Couverture souple

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Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Enables even readers without knowledge of matrices to grasp their operations to learn multivariate data analysis in matrix formsEmphasizes what model underlies an analysis procedure and what function is optimized for estimatin. N� de r�f. du vendeur 449935627

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