Multivariate Statistical Methods - Going Beyond the Linear (Hardcover, 1st ed. 2021)

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.

General

Imprint:	Springer Nature Switzerland AG
Country of origin:	Switzerland
Series:	Frontiers in Probability and the Statistical Sciences
Release date:	October 2021
First published:	2021
Authors:	Gyoergy Terdik
Dimensions:	235 x 155mm (L x W)
Format:	Hardcover
Pages:	418
Edition:	1st ed. 2021
ISBN-13:	978-3-03-081391-8
Categories:	Books > Science & Mathematics > Mathematics > Probability & statistics Books > Computing & IT > Computer software packages > Other software packages > Mathematical & statistical software
LSN:	3-03-081391-6
Barcode:	9783030813918

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