Abstract
The main objective of this paper is to introduce a new class of estimators for the ill-conditioned beta regression model. The new class, named the Liu-ridge-type (LRT), incorporates two shrinkage parameters that allow it to include the maximum-likelihood estimator (MLE), the ridge estimator (RE), and the Liu estimator (LE) as special cases. The LRT estimator has been shown to outperform the LE, the RE, and the MLE in terms of the mean squared error (MSE) matrix under certain conditions. Simulated and real applications illustrate the potential benefits of the new LRT estimator.
Sign-in/Register to access full text options 
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 callDisclaimer: 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.
