Multivariate Statistical Methods
Going Beyond the Linear
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- 89٫99 US$
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- 89٫99 US$
وصف الناشر
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.
Statistical Analysis of Next Generation Sequencing Data
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Statistical Methods for Ranking Data
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Random Toeplitz Functionals and Their Applications
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From Nonparametric Regression to Statistical Inference for Non-Ergodic Diffusion Processes
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Sharp Inequalities for Ordered Random Variables in Statistics and Reliability
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Introduction to the Statistics of Poisson Processes and Applications
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