Abstract

In this article we consider the problem of estimating the coefficient vector of a classical regression model when it is apriori suspected that the parameters vector may belong to a subspace. Two estimators; namely the positive-part of Stein-type estimator and the improved preliminary test estimator are proposed and it is demonstrated analytically as well as numerically that the proposed estimators dominate the usual Stein-type and pretest estimators respectively. The proposed estimators are also compared in terms of risks with that of the unrestricted estimator and we find that the positive-part of Stein-type estimator uniformly dominates the unrestricted estimator while the improved preliminary test estimator dominates the unrestricted estimator in a wider range than that of the usual pretest estimator.

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.