A Generalized Exponential Type Estimator of Population Mean in the Presence of Non-Response

Muneer, Siraj; Shabbir, Javid; Khalil, Alamgir

doi:10.21307/stattrans-2018-015

Cited by 4 publications

(3 citation statements)

References 15 publications

(29 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Sharma and Pal (2018) proposed improved ratio type estimator for the estimation of population mean in presence of random non-response. Muneer et al (2018) suggested a generalized exponential ratio type estimator of population mean in the presence of non-response Toutenberg and Srivastava (1998); Toutenberg and Srivastava (2003) studied the problem of estimation of ratio of two population means and the population mean respectively in survey sampling when some observations are missing on study and auxiliary variables. Sinha (2007, 2009) also suggested enhanced estimation of the ratio of the two population means using multi auxiliary characteristics in the presence of non-response.…”

Section: Introductionmentioning

confidence: 99%

Dexterous Estimation of Population Mean in Survey Sampling Under Non-Response Error

Yadav

2019

Int J Math, Eng, Manag Sci

View full text Add to dashboard Cite

In this scripture, we ponder the problem of efficient estimation of population mean of study variable utilizing information on highly correlated auxiliary variables under the presence of non-response on either of the variables. For this purpose, we suggest, an improved estimator under three different situations of non-response. Under the first situation, estimation of population mean is done with the problem of non-response on both the study and the auxiliary variables with the additional condition that the population means of the auxiliary variables are known. The second situation is to estimate the population mean of primary variable when the problem of non-response is only on the primary variable but the population means of the auxiliary variables are known while under the third situation estimation is performed with the problem of non-response on both the study and the auxiliary variables but population mean of one of the auxiliary variables is unknown. We study the sampling properties of the suggested estimator under above three different situations of non-response. We compare the proposed estimator with the competing estimators of population mean, under three different situations of non-response. The efficiency conditions are obtained for all three situations. A numerical study is also carried out to verify the efficiency conditions.

show abstract

Section: Introductionmentioning

confidence: 99%

Dexterous Estimation of Population Mean in Survey Sampling Under Non-Response Error

Yadav

2019

Int J Math, Eng, Manag Sci

View full text Add to dashboard Cite

show abstract

“…In the context of nonrespond, [11] introduced an elevated ratio estimator for estimating Ȳ. For the issue of non-respond, [12] proposed an exponential type generalized estimator of Ȳ. While some observations on Y and X are missing, [13,14] investigated the challenge of estimating the ratio of two Ȳ in survey sampling.…”

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

“…After Singh et al [16], Kumar and Bhougal [28], Kumar [29], Yadav et al [22], Pal and Singh [20], Singh and Usman [19], Ünal and Kadilar [30,31], Muneer et al [32], Sanaullah et al [26], Riaz et al [33], Sinha and Kumar [23], Pal and Singh [24], Kumar and Kumar [25] and Sanaullah et al [26] also proposed new estimators, taking advantage of an exponential function for Case II.…”

Section: Introductionmentioning

confidence: 99%

A New Family of Exponential Type Estimators in the Presence of Non-Response

Ünal

Kadılar

2021

J. Math. Fund. Sci.

View full text Add to dashboard Cite

We propose families of estimators for the population mean using an exponential function in case of non-response. This situation is examined under two cases, Case I and II. The bias, MSE and minimum MSE are separately obtained for both cases. We compare the proposed estimators theoretically with the main estimators from the literature, such as Hansen and Hurwitz (1946), ratio, regression and exponential estimators. The conditions for which the proposed estimators are most efficient are obtained. Moreover, different empirical studies are conducted to support the theoretical results for both cases.

show abstract

A Generalized Exponential Type Estimator of Population Mean in the Presence of Non-Response

Cited by 4 publications

References 15 publications

Dexterous Estimation of Population Mean in Survey Sampling Under Non-Response Error

Dexterous Estimation of Population Mean in Survey Sampling Under Non-Response Error

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

A New Family of Exponential Type Estimators in the Presence of Non-Response

Contact Info

Product

Resources

About