Estimation in a simple linear regression model with measurement error

2018/04/09 by Tsukuma, Hisayuki
#FOS: Mathematics #Statistics Theory (math.ST)

paper · doi:10.48550/arxiv.1804.03029

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.

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