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Applied regularization methods for the social sciences

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Applied regularization methods for the social sciences/ Holmes Finch.
作者:	Finch, W. Holmes
出版者:	Boca Raton, FL :CRC Press, : 2022.,
面頁冊數:	1 online resource.
標題:	R (Computer program language) -
電子資源:	https://www.taylorfrancis.com/books/9780367809645
ISBN:	9780367809645

Applied regularization methods for the social sciences
Finch, W. Holmes

Applied regularization methods for the social sciences[electronic resource] /Holmes Finch. - 1st ed. - Boca Raton, FL :CRC Press,2022. - 1 online resource. - Chapman & Hall/CRC, statistics in the social and behavioral sciences ceries. - Chapman & Hall/CRC, statistics in the social and behavioral sciences ceries..

Includes bibliographical references and index.

R -- Theoretical underpinnings of regularization methods -- Regularization methods for linear models -- Regularization methods for generalized linear models -- Regularization methods for multivariate linear models -- Regularization methods for cluster analysis and principal components analysis -- Regularization methods for latent variable models -- Regularization methods for multilevel models.

"Researchers in the social sciences are faced with complex data sets in which they have relatively small samples and many variables (high dimensional data). Unlike the various technical guides currently on the market, Applied Regularization Methods for the Social Sciences provides and overview of a variety of models alongside clear examples of hands-on application. Each chapter in this book covers a specific application of regularization techniques with a user-friendly technical description, followed by examples that provide a thorough demonstration of the methods in action"--

ISBN: 9780367809645

LCCN: 2021048065Subjects--Topical Terms:

679069
R (Computer program language)

LC Class. No.: HA29

Dewey Class. No.: 300.1/5

Applied regularization methods for the social sciences
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504 $a Includes bibliographical references and index.
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520 $a "Researchers in the social sciences are faced with complex data sets in which they have relatively small samples and many variables (high dimensional data). Unlike the various technical guides currently on the market, Applied Regularization Methods for the Social Sciences provides and overview of a variety of models alongside clear examples of hands-on application. Each chapter in this book covers a specific application of regularization techniques with a user-friendly technical description, followed by examples that provide a thorough demonstration of the methods in action"-- $c Provided by publisher.
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