Applied regularization methods for the social sciences / Holmes Finch.

Author/creator Finch, W. Holmes
Format Electronic
EditionFirst edition.
Publication InfoBoca Raton : CRC Press, Taylor & Francis Group, 2022.
Description1 online resource
Supplemental ContentFull text available from eBooks on EBSCOhost
Supplemental ContentFull text available from Taylor & Francis eBooks
Subjects

Contents 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.
Abstract "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"-- Provided by publisher.
General note"A Chapman & Hall book."
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: Finch, W. Holmes Applied regularization methods for the social sciences First edition. Boca Raton : CRC Press, Taylor & Francis Group, 2022 9780367408787
Genre/formElectronic books.
LCCN 2021048065
ISBN9780367809645 (ebook)
ISBN(hardback)
ISBN(paperback)

Availability

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Electronic Resources ✔ Available