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• W2151911431 abstract "In this paper, we extend to generalized linear models the robust model selection methodology of Muller and Welsh (2005). As in Muller and Welsh (2005), we combine a robust penalized measure of fit to the sample with a robust measure of out of sample predictive ability that is estimated using a post-stratified m-out-of-n bootstrap. The method can be used to compare different estimators (robust and nonrobust) as well as different models. Specialized to linear models, the present methodology improves on Muller and Welsh (2005): we use a new bias-adjusted bootstrap estimator which avoids the need to include an intercept in every model and we establish an essential monotonicity condition more generally." @default.
• W2151911431 created "2016-06-24" @default.
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• W2151911431 date "2009-07-01" @default.
• W2151911431 modified "2023-09-23" @default.
• W2151911431 title "ROBUST MODEL SELECTION IN GENERALIZED LINEAR MODELS" @default.
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