Abstract
In this paper, the problem of estimation of finite population mean in stratified random sampling is considered. Two improved exponential logarithmic type calibration estimators for finite population mean have been proposed for stratified random sampling when auxiliary information related to variable under study is available for each stratum. To judge the performance of the proposed estimators, a simulation study has been carried out in R-software using two datasets, one real and another one artificial generated population. The proposed estimators have also been compared with the estimators developed by Bahl and Tuteja [1] and Singh [17] in case of stratified random sampling.
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.
