Estimation in a partially linear single-index model with missing response variables and error-prone covariates

Journal of inequalities and applications

Xin Qi¹ 

关键词: partially linear single-index model;    least-squared;    local linear regression;    imputation estimator;   

DOI  :  10.1186/s13660-015-0941-8

学科分类：数学（综合）

来源: SpringerOpen

【 摘 要 】

In this paper, the authors study the partially linear single-index model when the covariate X is measured with additive error and the response variable Y is sometimes missing. Based on the least-squared technique, an imputation method is proposed to estimate the regression coefficients, single-index coefficients, and the nonparametric function, respectively. Thereafter, asymptotical normalities of the corresponding estimators are proved. A simulation experiment and an application to a diabetes study are used to illustrate our proposed method.

【 授权许可】

CC BY