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Random Effect and Latent Variable Model Selection

Random effects and latent variable models are broadly used in analyses of multivariate data. These models can accommodate high dimensional data having a variety of measurement scales. Methods for model selection and comparison are needed in conducting hypothesis tests and in building sparse predicti...

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Bibliographic Details
Call Number:Libro Electrónico
Corporate Author: SpringerLink (Online service)
Other Authors: Dunson, David (Editor)
Format: Electronic eBook
Language:Inglés
Published: New York, NY : Springer New York : Imprint: Springer, 2008.
Edition:1st ed. 2008.
Series:Lecture Notes in Statistics, 192
Subjects:
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