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Mixture Models: Parametric, Semiparametric, and New Directions (Chapman & Hall/CRC Monographs on Statistics and Applied Probability)

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Description

Mixture models are a powerful tool for analyzing complex and heterogeneous datasets across many scientific fields, from finance to genomics. Mixture Models: Parametric, Semiparametric, and New Directions provides an up-to-date introduction to these models, their recent developments, and their implementation using R. It fills a gap in the literature by covering not only the basics of finite mixture models, but also recent developments such as semiparametric extensions, robust modeling, label switching, and high-dimensional modeling. Features Comprehensive overview of the methods and applications of mixture models Key topics include hypothesis testing, model selection, estimation methods, and Bayesian approaches Recent developments, such as semiparametric extensions, robust modeling, label switching, and high-dimensional modeling Examples and case studies from such fields as astronomy, biology, genomics, economics, finance, medicine, engineering, and sociology Integrated R code for many of the models, with code and data available in the R Package MixSemiRob Mixture Models: Parametric, Semiparametric, and New Directions is a valuable resource for researchers and postgraduate students from statistics, biostatistics, and other fields. It could be used as a textbook for a course on model-based clustering methods, and as a supplementary text for courses on data mining, semiparametric modeling, and high-dimensional data analysis.

Product Specifications

Format: Hardcover
ASIN: 0367481820
Category: Books > Subjects > Science, Nature & Maths > Mathematics > Modelling
Domain: Amazon UK
Release Date: 05 April 2022
Listed Since: 12 October 2023

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Mixture Models: Parametric, Semiparametric, and New Directions (Chapman & Hall/CRC Monographs on Statistics and Applied Probability)

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