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Journals / Hacettepe Journal of Mathematics and Statistics / 2008 / Cilt: 37 - Sayı: 1

Variance estimation in simple random sampling using auxiliary information

Sat GUPTA
Javid SHABBIR
Pages
57–67
Publication Date
2022-10-18
DOI
—
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Four numerical examples are considered to further evaluate the performance of these estimators.

📌 3 Key Takeaways

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Objective & Hypothesis:In this paper we focus on investigating the precision of several variance estimators considered by different authors, such as those suggested by Isaki (Variance estimation using auxiliary information, J.
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Key Findings & Data:Assoc. 78, 117–123, 1983), and Kadilar and Cingi (Ratio estimators for population variance in simple and stratified sampling, Appl.
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Conclusion & Impact:Four numerical examples are considered to further evaluate the performance of these estimators.
🔬Design:Research Article
📍Scope:2006 Verileri
⚙️Variables:Domain Parameters

Abstract

In this paper we focus on investigating the precision of several variance estimators considered by different authors, such as those suggested by Isaki (Variance estimation using auxiliary information, J. Amer. Stat. Assoc. 78, 117–123, 1983), and Kadilar and Cingi (Ratio estimators for population variance in simple and stratified sampling, Appl. Math. Comp. 173, 1047–1058 and Improvement in variance estimation using auxiliary information, Hacet. J. Math. Stat. 35 (1), 111–115, 2006). We propose a new hybrid class of estimators and show that in some cases their efficiency is better than the aforementioned traditional ratio and regression estimators of Isaki, and Kadilar and Cingi. Four numerical examples are considered to further evaluate the performance of these estimators.

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Cite This Article

GUPTA, S., SHABBIR, J. (2022). Variance estimation in simple random sampling using auxiliary information. Hacettepe Journal of Mathematics and Statistics, Cilt: 37 - Sayı: 1, 57–67. https://ajindex.com/articles/530715

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References (10)

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