Empirical Likelihood-Based Inferences for Generalized Partially Linear Models

Abstract

This paper considers generalized partially linear models. We propose empirical likelihood-based statistics to construct confidence regions for the parametric and non-parametric components. The resulting statistics are shown to be asymptotically chi-square distributed. Finite-sample performance of the proposed statistics is assessed by simulation experiments. The proposed methods are applied to a data set from an AIDS clinical trial. Copyright (c) 2009 Board of the Foundation of the Scandinavian Journal of Statistics.