Abstract
In this article, various classical estimation methods are employed to estimate the parameters of unit Burr III distribution. Further, the associated second-order bias corrections of the MLEs of its parameters are obtained by using a modified bias-corrected approach. In addition, another parametric bootstrap bias correction method is also considered for model parameters. Extensive Monte-Carlo simulation studies are performed to evaluate different estimation methods in terms of their average biases and mean squared error, and the performance of these estimators are compared as well. Our results reveal that the bias corrections improve the accuracy of maximum likelihood estimates. Finally, one real data example is discussed to illustrate the applicability of the unit Burr III distribution.
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 callMore From: American Journal of Mathematical and Management Sciences
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.
