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Multivariate Statistical Methods : Going Beyond the Linear - György Terdik

Multivariate Statistical Methods

Going Beyond the Linear

By: György Terdik

eText | 26 October 2021

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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.

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Non-FictionMathematicsProbability & StatisticsComputing & I.T.Business ApplicationsMathematical & Statistical Software

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