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Estimation of the intercept parameter for linear regression model with uncertain non-sample prior information
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Estimation of the intercept parameter for linear regression model with uncertain non-sample prior information
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Estimation of the intercept parameter for linear regression model with uncertain non-sample prior information
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Journal Article
Estimation of the intercept parameter for linear regression model with uncertain non-sample prior information
2005
Overview
This paper considers alternative estimators of the intercept parameter of the linear regression model with normal error when uncertain non-sample prior information about the value of the slope parameter is available. The maximum likelihood, restricted, preliminary test and shrinkage estimators are considered. Based on their quadratic biases and mean square errors the relative performance of the estimators are investigated. Both analytical and graphical comparisons are explored. None of the estimators is found to be uniformly dominating the others. However, if the non-sample prior information regarding the value of the slope is not too far from its true value, the shrinkage estimator of the intercept parameter dominates the rest of the estimators. [PUBLICATION ABSTRACT]
Publisher
Springer Nature B.V
Subject
