Some Improved Classes of Estimators in Stratified Sampling Using Bivariate Auxiliary Information

This manuscript considers some improved combined and separate classes of estimators of population mean using bivariate auxiliary information under stratified simple random sampling. The expressions of bias and mean square error of the proposed classes of estimators are determined to the first order...

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Bibliographic Details
Published in:Journal of probability and statistics 2022-08, Vol.2022, p.1-23
Main Authors: Bhushan, Shashi, Kumar, Anoop, Onyango, Ronald, Singh, Saurabh
Format: Article
Language:English
Subjects:
Bias
Bivariate analysis
Calibration
COVID-19
Estimators
Population
Random sampling
Variables
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Summary:This manuscript considers some improved combined and separate classes of estimators of population mean using bivariate auxiliary information under stratified simple random sampling. The expressions of bias and mean square error of the proposed classes of estimators are determined to the first order of approximation. It is exhibited that under some particular conditions, the proposed classes of estimators dominate the existing prominent estimators. The theoretical findings are supported by a simulation study performed over a hypothetically generated population.
ISSN:1687-952X
1687-9538
DOI:10.1155/2022/2660114