The optimal extended balanced loss function estimators

作者:

Highlights:

摘要

We derive the optimal heterogeneous, homogeneous and homogeneous unbiased estimators of the coefficient vector in a linear regression model under the extended balanced loss function of Shalabh et al. (2009). Risk functions and optimal predictors of the new estimators are evaluated and comparisons among the estimators are made with respect to the extended balanced loss function. Some of the theoretical results are illustrated by a numerical example. Moreover, the behavior of the proposed estimators is studied via a Monte-Carlo experiment in the sense of mean square error.

论文关键词:Linear model,Estimation,Extended balanced loss function,Optimal heterogeneous estimator,Optimal homogeneous estimator,Prediction mean square error

论文评审过程:Received 15 June 2016, Revised 1 December 2017, Available online 22 June 2018, Version of Record 30 June 2018.

论文官网地址:https://doi.org/10.1016/j.cam.2018.06.021