主  題: Integrated Likelihood Inference In Semiparametric Regression Models 

內(nèi)容簡(jiǎn)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.

報(bào)告人: 何和平   教授    博導(dǎo)

時(shí)  間: 2018-06-05    15:30 

地  點(diǎn): 競(jìng)慧東樓305 

舉辦單位: 統(tǒng)計(jì)與數(shù)學(xué)學(xué)院、統(tǒng)計(jì)科學(xué)與大數(shù)據(jù)研究院