Multivariate Statistical Methods: Going Beyond the Linear

By György Terdik

Book Overview

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.

• Format: Paperback
• Language: English
• ISBN: B0BGX12RQQ
• ISBN13: 9783030813949
• Release Date: October 2022
• Publisher: Springer
• Length: 418 Pages
• Weight: 1.33 lbs.
• Dimensions: 0.9" x 6.1" x 9.2"