Title Statements
- Full title :Multivariate Statistical Methods : Going Beyond the Linear / György Terdik [aut]
Summary
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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- Publication Date:2021
Publication Statements
- Publisher(s):Springer International Publishing
- Place of Publication:Cham
- Language:eng
- Publication Date:2021
The Physical Object
- Description:1 online resource
Edition Identifiers
- ISBN:9783030813925, 3030813924, 9783030813932, 3030813932, 9783030813949, 3030813940, 9783030813918, 3030813916
- DOI:10.1007/978-3-030-81392-5
- oclc:on1346715367
Table of Contents
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.
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