主  題: Variance Estimation for Semiparametric Regression Models by Local Averaging

內(nèi)容簡(jiǎn)介: Variance   estimation is a fundamental problem in statistical modelling and plays an   important role in the inferences after model selection and estimation. In   this paper, we focus on several nonparametric and semiparametric models, and   propose a local averaging method for variance estimation based on the concept   of partial consistency.

The   proposed method has the advantages of avoiding the estimation of the   nonparametric function and reducing the computational cost and can be easily   extended to more complex settings.    Asymptotic normality is established for the proposed local averaging   estimators. Numerical simulations and real data analyse are presented to   illustrate the finite sample performance of the proposed method.

報(bào)告人: 彭衡      副教授

時(shí)  間: 2017-10-25    13:30

地  點(diǎn): 位育樓117

舉辦單位: 經(jīng)濟(jì)與金融研究院  科研部