Scholion.ai

Testing generalized linear and semiparametric models against smooth alternatives

Göran Kauermann, Gerhard Tutz

Journal of the Royal Statistical Society: Series B (Statistical Methodology) · 2001 · Volume 63 · Issue 1

DOI: 10.1111/1467-9868.00281

Abstract

We propose goodness-of-fit tests for testing generalized linear models and semiparametric regression models against smooth alternatives. The focus is on models having both continous and factorial covariates. As a smooth extension of a parametric or semiparametric model we use generalized varying-coefficient models as proposed by Hastie and Tibshirani. A likelihood ratio statistic is used for testing. Asymptotic expansions allow us to write the estimates as linear smoothers which in turn guarantees simple and fast bootstrapping of the test statistic. The test is shown to have √n-power, but in contrast with parametric tests it is powerful against smooth alternatives in general.

Keywords

Likelihood ratio, Local likelihood fitting, Model checking, Semiparametric models, Smoothing

Enable JavaScript for citation tools and additional paper interactions.