Empirical Likelihood‐Based Inferences for Generalized Partially Linear Models

Abstract

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.