Ebook: Multivariate Statistical Methods: Going Beyond The Linear
Author: György Terdik
- Genre: Mathematics // Mathematicsematical Statistics
- Tags: Statistical Theory And Methods Statistics And Computing: Statistics Programs
- Series: Frontiers In Probability And The Statistical Sciences
- Year: 2021
- Publisher: Springer
- Edition: 1
- Language: English
- pdf
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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