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Book synopsis

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.

Book details

• Full title: Multivariate Statistical Methods
• Author: György Terdik
• Language: English
• Binding: Hardback
• Number of pages: 432
• EAN: 9783030813918
• ISBN: 3030813916
• ID: 37347381
• Publisher: Springer Nature Switzerland AG
• Weight: 811 g
• Dimensions: 241 × 160 × 29 mm
• Date of publishing: 27. October 2021

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