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Multivariate statistical methodsgoing beyond the linear /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Multivariate statistical methodsby Gyorgy Terdik.
Reminder of title:	going beyond the linear /
Author:	Terdik, Gyorgy.
Published:	Cham :Springer International Publishing :2021.
Description:	xiv, 418 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	Multivariate analysis.
Online resource:	https://doi.org/10.1007/978-3-030-81392-5
ISBN:	9783030813925$q(electronic bk.)

Multivariate statistical methodsgoing beyond the linear /
Terdik, Gyorgy.

Multivariate statistical methodsgoing beyond the linear /[electronic resource] :by Gyorgy Terdik. - Cham :Springer International Publishing :2021. - xiv, 418 p. :ill., digital ;24 cm. - Frontiers in probability and the statistical sciences,2624-9995. - Frontiers in probability and the statistical sciences..

Some Introductory Algebra -- Tensor derivative of vector functions -- T-Moments and T-Cumulants -- Gaussian systems, T-Hermite polynomials, Moments and Cumulants -- Multivariate Skew Distributions -- Multivariate skewness and kurtosis.

This book presents a general method for deriving higher-order statistics of multivariate distributions with simple algorithms that allow for actual calculations. Multivariate nonlinear statistical models require the study of higher-order moments and cumulants. The main tool used for the definitions is the tensor derivative, leading to several useful expressions concerning Hermite polynomials, moments, cumulants, skewness, and kurtosis. A general test of multivariate skewness and kurtosis is obtained from this treatment. Exercises are provided for each chapter to help the readers understand the methods. Lastly, the book includes a comprehensive list of references, equipping readers to explore further on their own.

ISBN: 9783030813925$q(electronic bk.)

Standard No.: 10.1007/978-3-030-81392-5doiSubjects--Topical Terms:

181905
Multivariate analysis.

LC Class. No.: QA278 / .T47 2021

Dewey Class. No.: 519.535

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490 1 $a Frontiers in probability and the statistical sciences, $x 2624-9995
505 0 $a Some Introductory Algebra -- Tensor derivative of vector functions -- T-Moments and T-Cumulants -- Gaussian systems, T-Hermite polynomials, Moments and Cumulants -- Multivariate Skew Distributions -- Multivariate skewness and kurtosis.
520 $a This book presents a general method for deriving higher-order statistics of multivariate distributions with simple algorithms that allow for actual calculations. Multivariate nonlinear statistical models require the study of higher-order moments and cumulants. The main tool used for the definitions is the tensor derivative, leading to several useful expressions concerning Hermite polynomials, moments, cumulants, skewness, and kurtosis. A general test of multivariate skewness and kurtosis is obtained from this treatment. Exercises are provided for each chapter to help the readers understand the methods. Lastly, the book includes a comprehensive list of references, equipping readers to explore further on their own.
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