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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.
Key Features:
Informazioni sull?autore:
Holmes Finch is the George and Frances Ball Distinguished Professor of Educational Psychology at BSU, and a professor of statistics and psychometrics. His research interests include structural equation modeling, item response theory, educational and psychological measurement, multilevel modeling, machine learning, and robust multivariate inference. In addition to conducting research in the field of statistics, he also regularly collaborates with colleagues in fields such as educational psychology, neuropsychology, and exercise physiology.
Titolo: Applied Regularization Methods for the ...
Casa editrice: CRC Press
Data di pubblicazione: 2024
Legatura: PAP
Condizione: New
Da: moluna, Greven, Germania
Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Holmes Finch is the George and Frances Ball Distinguished Professor of Educational Psychology at BSU, and a professor of statistics and psychometrics. His research interests include structural equation modeling, item response theory, educational and psyc. Codice articolo 1533112002
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Condizione: New. pages cm First edition Includes bibliographical references and index. Codice articolo 26397684826
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