Estimation in a simple linear regression model with measurement error
Statistics Theory
2018-04-10 v1 Statistics Theory
Abstract
This paper deals with the problem of estimating a slope parameter in a simple linear regression model, where independent variables have functional measurement errors. Measurement errors in independent variables, as is well known, cause biasedness of the ordinary least squares estimator. A general procedure for the bias reduction is presented in a finite sample situation, and some exact bias-reduced estimators are proposed. Also, it is shown that certain truncation procedures improve the mean square errors of the ordinary least squares and the bias-reduced estimators.
Cite
@article{arxiv.1804.03029,
title = {Estimation in a simple linear regression model with measurement error},
author = {Hisayuki Tsukuma},
journal= {arXiv preprint arXiv:1804.03029},
year = {2018}
}