Abstract
This study proposes a new class of regression cum ratio estimators, using transformation of the auxiliary variables. The expressions for the biases and mean squared errors of the new class of estimators are derived in the study. Both the theoretical and numerical comparison of the proposed estimators and their respective competitive estimators are made. To check the performance of estimators, a simulation study was performed. The performance of the new class of estimators was assessed and proven better in comparison to their competitive estimators.
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.
