A new population mean estimator under non-response cases

Ünal, Ceren; Kadılar, Cem

doi:10.1080/16583655.2022.2034343

Cited by 3 publications

(3 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…estimator following Singh et al (2008) study. Kumar (2013); Yunusa and Kumar (2014) and Unal and Kadilar (2021, 2022a, 2022b proposed estimators using exp. function for the estimating 𝑌 ̅ .…”

Section: Introductionmentioning

confidence: 99%

An Improvement in Estimating the Population Mean Based on Family of Estimators with Different Application Areas

ÜNAL,

KADILAR

2023

Gazi University Journal of Science Part A: Engineering and Innovation

Self Cite

View full text Add to dashboard Cite

In a sampling study, the complete information for the necessary variables may not always be available in practice. Therefore, the non-response situation has been considered for estimating the unknown population parameters with different types of estimators. The families of estimators are proposed for the population mean in the case of non-response under two different cases with the approach of an exponential function. Their properties are derived in detail. We compare these estimators with the main estimators in the literature to present the efficiencies, theoretically. Moreover, the three different empirical studies are illustrated and in that way, we found that the theoretical conclusion is supported by the obtained results numerically for each data set.

show abstract

Section: Introductionmentioning

confidence: 99%

An Improvement in Estimating the Population Mean Based on Family of Estimators with Different Application Areas

ÜNAL,

KADILAR

2023

Gazi University Journal of Science Part A: Engineering and Innovation

Self Cite

View full text Add to dashboard Cite

show abstract

“…Unal and Kadilar [27] proposed the estimators class for estimating Ȳ, utilizing exponential function in the nonresponse condition for a couple of cases. In the condition of nonresponse on Y and X, Unal and Kadilar [27] adopted an exponential type estimator for Ȳ. Unal and Kadsilar [30] introduced a new class of exponential estimators in the case of nonresponse and Unal and Kadilar [31] worked on a novel population mean estimator for the nonresponse problem. Jaiswal et al [32] suggested an elevated procedure for the estimation of population mean in the case of nonresponse.…”

Section: Introductionmentioning

confidence: 99%

“…Some recent contributions for elevated estimation of Ȳ for the nonresponse problem were made by Ahmed at al. [33], Yadav et al [34], Ahmed and Shabir [35], Hussain et al [36], Unal and Kadilar [30], and Ahmad et al [37].…”

Section: Introductionmentioning

confidence: 99%

Restructured searls family of estimators of population mean in the presence of nonresponse

Ahmadini

Yadav²,

Yadav³

et al. 2022

Front. Appl. Math. Stat.

View full text Add to dashboard Cite

Nonresponse is a major problem encountered by surveyors when conducting sampling surveys. The present study suggested a naïve modified Searls method for the elevated estimation of the population mean of the primary variable under investigation by utilizing the known auxiliary parameters. The bias along with the mean squared error (MSE) of the introduced estimator is calculated up to the approximation of the first order. We compared the presented estimator with a competing usual unbiased estimator and other competing population mean estimators regarding the issue of nonresponse. The efficiency criteria of the introduced estimator outperforming the other estimators in the competition are determined and verified using five real data sets. The MSEs for the introduced estimator and the other estimators in the competition are calculated for the five considered populations. The estimator with the least MSE or highest percentage relative efficiency (PRE) is recommended for practical exercise in different areas of applications.

show abstract

Evaluation of different estimator approaches based on COVID-19 data and a simulation study

Lone,

Unal,

Oncel Cekim

2024

Alexandria Engineering Journal

View full text Add to dashboard Cite

A new population mean estimator under non-response cases

Cited by 3 publications

References 12 publications

An Improvement in Estimating the Population Mean Based on Family of Estimators with Different Application Areas

An Improvement in Estimating the Population Mean Based on Family of Estimators with Different Application Areas

Restructured searls family of estimators of population mean in the presence of nonresponse

Evaluation of different estimator approaches based on COVID-19 data and a simulation study

Contact Info

Product

Resources

About