ABSTRACT
In this paper, the problem of estimation of mean through calibration technique has been discussed. In the current investigation, we proposed new calibrated estimators of mean in simple random sampling, probability proportional to size sampling and stratified random sampling by considering non-linear constraints of an auxiliary variable. It has been shown through simulation study that the resultant estimators are more efficient than the combined regression as well as the combined ratio estimator in all three sampling designs.
Acknowledgements
The authors are thankful to the Editor in Chief: Dr Richard Krutchkoff for bringing this paper in the final form. This work was done by the lead author Shameem Alam while visiting the Department of Mathematics, Texas AM University-Kingsville, Kingsville, TX with a scholarship (No:1-8/HEC/HRD/2018/8855) offered by the Higher Education Commission H-9 Islamabad, Pakistan.
Disclosure statement
No potential conflict of interest was reported by the authors.
ORCID
Shameem Alam http://orcid.org/0000-0002-2926-4283
Sarjinder Singh http://orcid.org/0000-0002-3138-9640
Javid Shabbir http://orcid.org/0000-0002-0035-7072