Partial Generalized Additive Models: An Information-Theoretic Approach for Dealing With Concurvity and Selecting Variables

Abstract

Scientists are often interested in which covariates are important, and how these covariates affect the response variable, rather than just making predictions. This requires inputs from both statistical modeling and background knowledge. Generalized additive models (GAMs) are a class of interpretable, multivariate nonparametric regression models which are… (More)

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Cite this paper

@inproceedings{Gu2010PartialGA, title={Partial Generalized Additive Models: An Information-Theoretic Approach for Dealing With Concurvity and Selecting Variables}, author={Hong Gu and Toby Kenney and Mu Zhu}, year={2010} }