主 题: Integrated Likelihood Inference In Semiparametric Regression Models
内容简介: Consider a semiparametric regression model with a p-dimensional parameter as the parameter of interest, and an unknown function as a nuisance parameter. An integrated likelihood is proposed for the model, eliminating the unknown function by averaging with respect to a Gaussian process. The maximum integrated likelihood estimator and its asymptotic normality are presented. This methodology is illustrated on examples and it can be extended to many other semiparametric models.
报告人: 何和平 教授 博导
时 间: 2018-06-05 15:30
地 点: 竞慧东楼305