Matrix-Based Introduction to Multivariate Data Analysis

Name: Matrix-Based Introduction to Multivariate Data Analysis
Brand: Springer Verlag, Singapore
SKU: 9789811095955
Price: 388.31 PLN
Availability: InStock

Autor: KOHEI ADACHI

Język:

Oprawa: Miękka

Wydawca: Springer Verlag, Singapore

Dostępność: Dostępna u dostawcy w małych ilościach

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This book enables readers who may not be familiar with matrices to understand a variety of multivari...

Informacje o książce

Autor

KOHEI ADACHI

Język

Angielski

Oprawa

Książka - Miękka

Data wydania

2018

strony

301

EAN

9789811095955

ISBN

9789811095955

Enbook ID

19416754

Wydawca

Springer Verlag, Singapore

Waga

486

Wymiary

155 x 235 x 15

Pełny opis

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.

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