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Performance evaluation of novel logarithmic estimators under correlated measurement errors

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  • Shashi Bhushan
  • Anoop Kumar
  • Shivam Shukla

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.

Suggested Citation

  • Shashi Bhushan & Anoop Kumar & Shivam Shukla, 2024. "Performance evaluation of novel logarithmic estimators under correlated measurement errors," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 53(15), pages 5353-5363, August.
    • Handle: RePEc:taf:lstaxx:v:53:y:2024:i:15:p:5353-5363
    DOI: 10.1080/03610926.2023.2219793
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