Statistical inference for the heteroscedastic partially linear varying-coefficient errors-in-variables model with missing censoring indicators
type: Item
instance of: scholarly article
title: Statistical inference for the heteroscedastic partially linear varying-coefficient errors-in-variables model with missing censoring indicators
zbMATH Open document ID: 1471.62307
DOI: 10.1155/2021/1141022
author: Yu-Ye Zou
author: Chengxin Wu
published in: Discrete Dynamics in Nature and Society
publication date: 2021-08-12T00:00:00Z
review text: Summary: In this paper, we focus on heteroscedastic partially linear varying-coefficient errors-in-variables models under right-censored data with censoring indicators missing at random. Based on regression calibration, imputation, and inverse probability weighted methods, we define a class of modified profile least square estimators of the parameter and local linear estimators of the coefficient function, which are applied to constructing estimators of the error variance function. In order to improve the estimation accuracy and take into account the heteroscedastic error, reweighted estimators of the parameter and coefficient function are developed. At the same time, we apply the empirical likelihood method to construct confidence regions and maximum empirical likelihood estimators of the parameter. Under appropriate assumptions, the asymptotic normality of the proposed estimators is studied. The strong uniform convergence rate for the estimators of the error variance function is considered. Also, the asymptotic chi-squared distribution of the empirical log-likelihood ratio statistics is proved. A simulation study is conducted to evaluate the finite sample performance of the proposed estimators. Meanwhile, one real data example is provided to illustrate our methods.
Mathematics Subject Classification ID: 62G05
Mathematics Subject Classification ID: 62N01
zbMATH DE Number: 7381258
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1155/2021/1141022
OpenAlex ID: W3169676151
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description: scientific article; zbMATH DE number 7381258