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

@inproceedings{Hong2010PartialGA,
  title={Partial Generalized Additive Models : An Information-Theoretic Approach for Dealing With Concurvity and Selecting Variables},
  author={Gu Ru Hong and Toby Kenney and Mu Zhu},
  year={2010}
}
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 very useful data exploration tools for these purposes, but concurvity among covariates (the nonlinear analogue of collinearity for linear… CONTINUE READING