Multivariate Statistical Methods : Going Beyond the Linear / by György Terdik

By:

Terdik, György [VerfasserIn]

Resource type: Ressourcentyp: Buch (Online)Book (Online)Language: English Series: Frontiers in Probability and the Statistical Sciences | Springer eBook CollectionPublisher: Cham : Springer, 2021Description: 1 Online-Ressource (XIV, 418 p.)ISBN:

9783030813925

Subject(s):

Additional physical formats: 9783030813918 | 9783030813932 | 9783030813949 | Erscheint auch als: 9783030813918 Druck-Ausgabe | Erscheint auch als: 9783030813932 Druck-Ausgabe | Erscheint auch als: 9783030813949 Druck-Ausgabe | Erscheint auch als: Multivariate statistical methods. Druck-Ausgabe Cham, 2021. xiv, 418 SeitenRVK: RVK: SK 830DOI: DOI: 10.1007/978-3-030-81392-5Online resources:

Summary: Some Introductory Algebra -- Tensor derivative of vector functions -- T-Moments and T-Cumulants -- Gaussian systems, T-Hermite polynomials, Moments and Cumulants -- Multivariate Skew Distributions -- Multivariate skewness and kurtosis.Summary: 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.PPN: PPN: 1775864731Package identifier: Produktsigel: ZDB-2-SEB | ZDB-2-SMA | ZDB-2-SXMS

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