Multivariate Statistical Methods / Frontiers in Probability and the Statistical Sciences (PDF)
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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.
His research interests include multivariate nonlinear statistics, time series analysis, modelling high speed communication networks, bilinear and multi-fractal models, directional statistics, and spherical processes, spatial dependence and interaction between space and time.
- Autor: György Terdik
- 2021, 1st ed. 2021, 418 Seiten, Englisch
- Verlag: Springer International Publishing
- ISBN-10: 3030813924
- ISBN-13: 9783030813925
- Erscheinungsdatum: 26.10.2021
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