Multivariate statistical methods : going beyond the linear : vector-moments and vector cumulants, nonlinear statistics of normal multivariates, testing skewness and kurtosis / György Terdik.

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Multivariate statistical methods : going beyond the linear : vector-moments and vector cumulants, nonlinear statistics of normal multivariates, testing skewness and kurtosis / György Terdik.

9783030813925 (electronic bk.)
3030813924 (electronic bk.)
9783030813918
3030813916

Cham : Springer, [2021]

©2021

English

1 online resource.

10.1007/978-3-030-81392-5 doi

QA278 .T47 2021

519.5/35

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.

Includes bibliographical references and index.

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Online resource; title from PDF title page (SpringerLink, viewed November 5, 2021).

Frontiers in probability and the statistical sciences.

Print version: 9783030813918

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