On Robustness of Resampling Estimators for Linear Regression Models

Abstract

The application of the resampling-approach to the linear regression model analysis is considered. The mean square estimators are known to be the best estimators in case of regression model without nuisance observations. Alternatively, in the case of model with nuisance observations called disturbed model the classical approach gives bad, biased estimators. The considered numerical example shows that the resampling-approach gives comparably good results for disturbed models