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Titlebook: Finite Mixture of Skewed Distributions; Víctor Hugo Lachos Dávila,Celso Rômulo Barbosa Cab Book 2018 The Author(s), under exclusive licens

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书目名称Finite Mixture of Skewed Distributions
编辑Víctor Hugo Lachos Dávila,Celso Rômulo Barbosa Cab
视频video
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
丛书名称SpringerBriefs in Statistics
图书封面Titlebook: Finite Mixture of Skewed Distributions;  Víctor Hugo Lachos Dávila,Celso Rômulo Barbosa Cab Book 2018 The Author(s), under exclusive licens
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
关键词regression models; measurement methods; bias detection; agreement; method validation
版次1
doihttps://doi.org/10.1007/978-3-319-98029-4
isbn_softcover978-3-319-98028-7
isbn_ebook978-3-319-98029-4Series ISSN 2191-544X Series E-ISSN 2191-5458
issn_series 2191-544X
copyrightThe Author(s), under exclusive license to Springer Nature Switzerland AG 2018
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