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Multivariate Statistical Methods: Going Beyond the Linear
Paperback
Series: Frontiers in Probability and the Statistical Sciences
ApplicationsProbability & Statistics
ISBN13: 9783030813949
Publisher: Springer Nature
Published: Oct 28 2022
Pages: 418
Weight: 1.33
Height: 0.88 Width: 6.14 Depth: 9.21
Language: English
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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