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.
- | Author: György Terdik
- | Publisher: Springer
- | Publication Date: Oct 28, 2022
- | Number of Pages: NA pages
- | Language: English
- | Binding: Misc. Supplies
- | ISBN-10: 3030813940
- | ISBN-13: 9783030813949
