Semiparametric likelihood ratio inference

Semiparametric Likelihood Ratio Inference Revisited

Semiparametric Likelihood Ratio Inference Revisited

2000 We extend the Semiparametric Likelihood Ratio Theorem of Murphy and Van del' Vaart for one-dimensional to Euclidean paramet(;rs of auy dimension. The as:VIrlptotic distribution of the likelihood ratio statistic for testing a k-dimensional Euclidean paramet'"r is shown to be the usual under the null hypothesis. This result is useful not only for testing purposes but also in forming likeliho...

Maximum likelihood estimation for semiparametric density ratio model.

In the statistical literature, the conditional density model specification is commonly used to study regression effects. One attractive model is the semiparametric density ratio model, under which the conditional density function is the product of an unknown baseline density function and a known parametric function containing the covariate information. This model has a natural connection with g...

Semiparametric likelihood inference for left-truncated and right-censored data.

This paper proposes a new estimation procedure for the survival time distribution with left-truncated and right-censored data, where the distribution of the truncation time is known up to a finite-dimensional parameter vector. The paper expands on the Vardis multiplicative censoring model (Vardi, 1989. Multiplicative censoring, renewal processes, deconvolution and decreasing density: non-parame...

Two-step generalised empirical likelihood inference for semiparametric models

This paper shows how generalised empirical likelihood can be used to obtain valid asymptotic inference for the …nite dimensional component of semiparametric models de…ned by a set of moment conditions. The results of the paper are illustrated using two well-known semiparametric regression models: the partially linear single index model and the linear transformation model with random censoring.