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International Journal of Creative and Open Research in Engineering and Management

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ISSN: 3108-1754 (Online)
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Volume 02, Issue 03

Published on: March 2026 2026

SYSTEMATIC REVIEW OF LITERATURE: SAMPLING ESTIMATORS

Pranjal Kaser

SoS in Statistics Pt. RSU Raipur C.G

Article Status

Plagiarism Passed Peer Reviewed Open Access

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Abstract

This paper reviews sampling estimators using auxiliary information to improve the accuracy of population estimates. Based on studies from 1946–2024, it covers classical estimators (ratio, regression, product) and recent advancements such as exponential, robust, and multi-auxiliary estimators. The review highlights theoretical developments, empirical findings, and emerging trends like machine learning and non-response handling. It also identifies research gaps in complex sampling designs and dynamic estimation, emphasizing the need for more efficient and adaptive estimators. Keywords: Ratio estimator, Regression estimator, sampling designs, multi- auxiliary information.

How to Cite this Paper

Kaser, P. (2026). Systematic Review of Literature: Sampling Estimators. International Journal of Creative and Open Research in Engineering and Management, <i>02</i>(03). https://doi.org/10.55041/ijcope.v2i3.181

Kaser, Pranjal. "Systematic Review of Literature: Sampling Estimators." International Journal of Creative and Open Research in Engineering and Management, vol. 02, no. 03, 2026, pp. . doi:https://doi.org/10.55041/ijcope.v2i3.181.

Kaser, Pranjal. "Systematic Review of Literature: Sampling Estimators." International Journal of Creative and Open Research in Engineering and Management 02, no. 03 (2026). https://doi.org/https://doi.org/10.55041/ijcope.v2i3.181.

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References


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  • Published on: Mar 30 2026
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