Hartley-Ross type estimators in simple random sampling

Kadılar, Cem; Çekim, Hatice Öncel

doi:10.1063/1.4912849

Cited by 5 publications

(2 citation statements)

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“…Then, the unbiased ratio estimators in the stratified random sampling were presented by Pascual [10]. Singh et al [11] and Kadilar and Cekim [4] proposed Hartley-Ross type unbiased estimators for the simple random sampling using various auxiliary information. Recently, Khan and Shabbir [7], [8] and Khan et al [9] have also suggested several Hartley-Ross type unbiased estimators under the ranked set sampling and the stratified ranked set sampling.…”

Section: Introduction and Notationsmentioning

confidence: 99%

Hartley-Ross type unbiased estimators using the Stratified Random Sampling

Çekim¹,

Kadılar²

2017

HJMS

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This study mentions Hartley-Ross type unbiased ratio estimators of the finite population mean in the stratified random sampling using the auxiliary variable. We propose a class of unbiased estimators using the estimators in Kadilar and Cingi [5], [6]. We derive the variance equations, up to the first degree of approximation, for all proposed estimators. The proposed estimators have been compared with the mentioned estimators in theory. Finally, we also demonstrate theoretical findings by the support of numerical illustrations.

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Section: Introduction and Notationsmentioning

confidence: 99%

Hartley-Ross type unbiased estimators using the Stratified Random Sampling

Çekim¹,

Kadılar²

2017

HJMS

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“…Later on, Pascual [14] proposed an unbiased ratio type estimator in stratified random sampling. Singh et al [19] and Kadilar and Cekim [9] suggested Hartley-Ross type unbiased estimators of finite population mean using the auxiliary information, such as the population coefficient of variation (C x ), coefficient of kurtosis (β 2x ) and the coefficient of correlation (ρ) in SRS. Recently Khan and Shabbir [10] suggested a class of Hartely-Ross type unbiased estimators in RSS.…”

Section: Introductionmentioning

confidence: 99%

Unbiased Ratio Estimators of the Mean in Stratified Ranked Set Sampling

Khan¹,

Shabbir²,

Gupta³

2016

HJMS

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Stratified ranked set sampling (StRSS) combines the advantages of stratification and ranked set sampling (RSS). In this paper, we propose several unbiased ratio type estimators using StRSS, when population mean of the auxiliary variable is known. The variances of the proposed unbiased ratio-type estimators are obtained to first degree of approximation. In simulation study the proposed estimators are more efficient as compared to other competitor estimators using Percentage Relative Efficiency (P RE), Percentage Relative Bias (P RB) and Percentage Relative Root Mean Square Error (P RRM SE).

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Improved population mean estimator with exponential function under non-response

Ünal,

Kadilar

2023

Appl. Math. J. Chin. Univ.

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Hartley-Ross type estimators in simple random sampling

Cited by 5 publications

References 0 publications

Hartley-Ross type unbiased estimators using the Stratified Random Sampling

Hartley-Ross type unbiased estimators using the Stratified Random Sampling

Unbiased Ratio Estimators of the Mean in Stratified Ranked Set Sampling

Improved population mean estimator with exponential function under non-response

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