| 書目名稱 | Finite Mixture of Skewed Distributions |
| 編輯 | Víctor Hugo Lachos Dávila,Celso R?mulo Barbosa Cab |
| 視頻video | http://file.papertrans.cn/344/343635/343635.mp4 |
| 概述 | Uses a flexible class of probability distributions for modeling data with skewness behavior, discrepant observations and population heterogeneity instead nonparametric methods.Explores methods that ar |
| 叢書名稱 | SpringerBriefs in Statistics |
| 圖書封面 |  |
| 描述 | This book presents recent results in finite mixtures of skewed distributions to prepare readers to undertake mixture models using scale mixtures of skew normal distributions (SMSN). For this purpose, the authors consider maximum likelihood estimation for univariate and multivariate finite mixtures where components are members of the flexible class of SMSN distributions. This subclass includes the entire family of normal independent distributions, also known as scale mixtures of normal distributions (SMN), as well as the skew-normal and skewed versions of some other classical symmetric distributions: the skew-t (ST), the skew-slash (SSL) and the skew-contaminated normal (SCN), for example. These distributions have heavier tails than the typical normal one, and thus they seem to be a reasonable choice for robust inference. The proposed EM-type algorithm and methods are implemented in the R package mixsmsn, highlighting the applicability of the techniques presented in the book..This work is a useful reference guide for researchers analyzing heterogeneous data, as well as a textbook for a graduate-level course in mixture models. The tools presented in the book make complex techniques a |
| 出版日期 | Book 2018 |
| 關鍵詞 | regression models; measurement methods; bias detection; agreement; method validation |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-3-319-98029-4 |
| isbn_softcover | 978-3-319-98028-7 |
| isbn_ebook | 978-3-319-98029-4Series ISSN 2191-544X Series E-ISSN 2191-5458 |
| issn_series | 2191-544X |
| copyright | The Author(s), under exclusive license to Springer Nature Switzerland AG 2018 |
|Archiver|手機版|小黑屋|
派博傳思國際
( 京公網(wǎng)安備110108008328)
GMT+8, 2025-10-15 15:44
發(fā)表于 2025-3-21 17:14:47
