Estimation and test of restricted linear EV model with nonignorable missing covariates  

作　　者：TANG Lin-jun ZHENG Sheng-chao ZHOU Zhan-gong 

机构地区：[1]Department of Statistics, Jiaxing University

出　　处：《Applied Mathematics(A Journal of Chinese Universities)》2018年第3期344-358,共15页高校应用数学学报（英文版）（B辑）

基　　金：Supported by the Zhejiang Provincial Natural Science Foundation of China(LY15A010019);National Natural Science Foundation of China(11501250)

摘　　要：This paper deals with estimation and test procedures for restricted linear errors-invariables(EV) models with nonignorable missing covariates. We develop a restricted weighted corrected least squares(WCLS) estimator based on the propensity score, which is fitted by an exponentially tilted likelihood method. The limiting distributions of the proposed estimators are discussed when tilted parameter is known or unknown. To test the validity of the constraints,we construct two test procedures based on corrected residual sum of squares and empirical likelihood method and derive their asymptotic properties. Numerical studies are conducted to examine the finite sample performance of our proposed methods.This paper deals with estimation and test procedures for restricted linear errors-invariables(EV) models with nonignorable missing covariates. We develop a restricted weighted corrected least squares(WCLS) estimator based on the propensity score, which is fitted by an exponentially tilted likelihood method. The limiting distributions of the proposed estimators are discussed when tilted parameter is known or unknown. To test the validity of the constraints,we construct two test procedures based on corrected residual sum of squares and empirical likelihood method and derive their asymptotic properties. Numerical studies are conducted to examine the finite sample performance of our proposed methods.

关 键 词：errors-in-variables model nonignorable missing data propensity score smoothed empirical likelihood 

分 类 号：O1[理学—数学]