Generalized Exponential Estimators of Finite Population Mean Using Transformed Auxiliary Variables

Yasmeen, Uzma; Amin, Muhammad Noor ul; Hanif, Muhammad

doi:10.1007/s40819-015-0034-x

Cited by 8 publications

(4 citation statements)

References 7 publications

(10 reference statements)

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“…Following Yasmeen et al (2015), a generalized dual to exponential ratio type estimator under non response is proposed. The bias and MSE expression of the proposed estimator has been derived.…”

Section: The Proposed Estimatormentioning

confidence: 99%

Promoting Statistical Practice and Collaboration in Developing Countries

Awe¹,

Love²,

Vance³

2022

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Section: The Proposed Estimatormentioning

confidence: 99%

Promoting Statistical Practice and Collaboration in Developing Countries

Awe¹,

Love²,

Vance³

2022

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“…When X 1 = X 2 such as for variance estimation in (Muneer, Khalil, Shabbir, and Narjis, 2018), this is a particular case of the additive parametric ratio estimator introduced just above. The third one is related to (Yasmeen, Amin, and Hanif, 2015;Adichwal, Sharma, and Singh, 2017). See for a comparison of this kind of estimators.…”

Section: Exemples Of Generalized Estimatorsmentioning

confidence: 99%

Visualization of generalized mean estimators using auxiliary information in survey sampling

Priam

2019

Communications in Statistics - Theory and Methods

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“…Many authors improved the precision of ratio and product estimators given in (1-2) by modifying them in different scenarios. For example, (Kadilar and Cingi, 2003) gave the stratified version of (Sisodia and Dwivedi, 1981; Upadhyaya and Singh, 1999), similarly (Kadilar and Cingi, 2005) extended the version of (Prasad, 1989) from simple random sampling (SRS) to StS, (Koyuncu and Kadilar, 2009) adopted the general family of estimators of (Khoshnevisan, et al, 2007;Searls, 1964) to StS, (Yasmeen, Noor-ul-Amin, and Hanif, 2015) gave a generalized exponential estimator for population mean using transformed auxiliary variable, (Malik and Singh, 2017) suggested exponential-type estimators with two auxiliary variables in StS, (Kumar, Trehan, and Joorel, 2018) gave the population mean estimate using two auxiliary variables by considering the impact of meansurment error and in the presence of non-response, (Noor-ul-Amin, Asghar, Sanaullah, and Shehzad, 2018) proposed a robust estimator using redescending M-estimator using auxiliary information. (Raza, Noor-ul-Amin, and Hanif, 2019) proposed a regression in ratio estimator in the existence of outliers using redescending M-Esimator, (Saini and Kumar, 2019) gave the transformed version of StS and stratified ranked set sampling to estimate the mean of the population.…”

Section: Introductionmentioning

confidence: 99%

Memory Type Ratio and Product Estimators in Stratified Sampling

Aslam

Noor-ul-Amin

Yasmeen

et al. 2020

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The exponential weighted moving average (EWMA) statistic is utilized the past information along with the present to enhance the efficiency of the estimators of the population parameters. In this study, the EWMA statistic is used to estimate the population mean with auxiliary information. The memory type ratio and product estimators are proposed under stratified sampling (StS). Mean square errors (MSE) expressions and relative efficiencies of the proposed estimators are derived. An extensive simulation study is conducted to evaluate the performance of the proposed estimators. An empirical study is presented based on real-life data that supports the findings of the simulation study.

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Generalized Exponential Estimators of Finite Population Mean Using Transformed Auxiliary Variables

Cited by 8 publications

References 7 publications

Promoting Statistical Practice and Collaboration in Developing Countries

Promoting Statistical Practice and Collaboration in Developing Countries

Visualization of generalized mean estimators using auxiliary information in survey sampling

Memory Type Ratio and Product Estimators in Stratified Sampling

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