Fall 2002 Seminar Series - November 14, 2002
University of Minnesota
School of Statistics
College of Liberal Arts
The In-and-Out-of-Sample (IOS)Likelihood Ratio Test for
Model Misspecification
Brett Presnell
Department of Statistics
University of Florida
Thursday, November 14, 2002
4:00 PM, 115
Ford Hall
Minneapolis, East Bank Campus
Social at 3:30 PM, 300
Ford Hall
Abstract
A new test of model misspecification is proposed, based
on the ratio of in-sample and out-of-sample likelihoods. The test is broadly
applicable, and in simple problems approximates well-known, intuitive methods.
Using jackknife influence curve approximations, it is shown that the test
statistic can be viewed asymptotically as a multiplicative contrast between
two estimates of the information matrix that are equal under correct model
specification. This approximation is used to show that the statistic is
asymptotically normally distributed, though it is suggested that p-values
be computed using the parametric bootstrap. The resulting methodology is
demonstrated with a variety of examples and simulations involving both
discrete and continuous data. This is joint work with Dennis Boos of North
Carolina State University.