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Springer Multivariate Statistical Methods: Going Beyond the Linear (Frontiers in Probability and the Statistical Sciences)

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Description

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.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
27 October 2021
Listed Since
11 June 2021

Barcode

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