Evaluating Accuracy in Mean Estimation with Post-Stratified Sampling
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Authors
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Hilal A. Lone
Lovely Professional University, Jalandhar
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Med Ram Verma
ICAR-Indian Agricultural Statistics Research Institute, New Delhi
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Monika Arora
Lovely Professional University, Jalandhar
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Manzoor A. Khanday
Lovely Professional University, Jalandhar
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Vijay Bahadur Sharma
MJFCVAS, Chomu, Jaipur, Rajasthan
Keywords:
MSE; Bias; Post StratificationAbstract
Accurately estimating the population mean under post-stratification can be difficult particularly in presence of auxiliary information. This study
introduces tc a separate ratio–cum–product estimator that uses two auxiliary variables, x and z to improve estimation precision. First-order
approximations are used to calculate bias and mean squared error and comparisons with conventional ratio, product, and Lone and Tailor (2014, 2015)
estimators. Empirical simulations confirm that tc consistently reduces MSE and enhances efficiency, demonstrating its practical value for statistical
applications in post-stratified surveys.
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