Performance evaluation of novel logarithmic estimators under correlated measurement errors
Shashi Bhushan,
Anoop Kumar and
Shivam Shukla
Communications in Statistics - Theory and Methods, 2024, vol. 53, issue 15, 5353-5363
Abstract:
In survey research, the issue of measurement errors (ME) has been sorted out by various authors, but the issue of correlated measurement errors (CME) has only been studied by Shalabh and Tsai (2017) till date. This article provides a modest acquaintance to evaluate the performance of few novel logarithmic estimators of population mean in the existence of CME under simple random sampling (SRS). The mean square error of the proposed estimators has been obtained. It has been exhibited theoretically under certain conditions that the proposed class of estimators dominates their conventional counterparts. Furthermore, the theoretical findings have been assessed with a Monte Carlo simulation using a hypothetically gendered population and proper suggestions have been forwarded to the survey professionals.
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:taf:lstaxx:v:53:y:2024:i:15:p:5353-5363
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DOI: 10.1080/03610926.2023.2219793
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