| 书目名称 | Multivariate Statistical Methods |
| 副标题 | Going Beyond the Lin |
| 编辑 | György Terdik |
| 视频video | |
| 概述 | Presents a general method for deriving higher order statistics of multivariate distributions.Discusses multivariate skewness and kurtosis; provides ready-to-use expressions for estimating and testing. |
| 丛书名称 | Frontiers in Probability and the Statistical Sciences |
| 图书封面 |  |
| 描述 | .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.. |
| 出版日期 | Book 2021 |
| 关键词 | Multivariate distributions; Skewness; Kurtosis; Cumulants; Hermite polynomials; Fourier transform; Multiva |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-3-030-81392-5 |
| isbn_softcover | 978-3-030-81394-9 |
| isbn_ebook | 978-3-030-81392-5Series ISSN 2624-9987 Series E-ISSN 2624-9995 |
| issn_series | 2624-9987 |
| copyright | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl |
发表于 2025-3-21 17:21:14
