Mixture models parametric, semiparametric, and new directions / Weixin Yao and Sijia Xiang.

Author/creator Yao, Weixin
Other author Xiang, Sijia.
Format Electronic
EditionFirst edition.
Publication InfoBoca Raton ; London : CRC Press, Taylor & Francis Group, 2024.
Description1 online resource ; illustrations
Supplemental ContentFull text available from eBooks on EBSCOhost
Subjects

SeriesChapman & Hall/CRC monographs on statistics and applied probability
Abstract "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"-- Provided by publisher.
Bibliography noteIncludes bibliographical references and index.
Access restrictionAvailable only to authorized users.
Technical detailsMode of access: World Wide Web
Source of descriptionDescription based on print version record and CIP data provided by publisher.
Issued in other formPrint version: Yao, Weixin. Mixture models First edition. Boca Raton ; London : CRC Press, Taylor & Francis Group, 2024 9780367481827
Genre/formElectronic books.
LCCN 2023047319
ISBN9781040009901 (epub)
ISBN9781003038511 (ebook)
ISBN(hardback)
ISBN(paperback)

Availability

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Electronic Resources Access Content Online ✔ Available