Predictive Estimation of Population Mean in Ranked Set Sampling

The article presents predictive estimation of population mean of the study variable in Ranked Set Sampling (RSS). It is shown that the predictive estimators in RSS using mean per unit estimator, ratio estimator and regression estimator as predictor for non-sampled values are equivalent to the corre...

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Main Authors: Shakeel Ahmed, Javid Shabbir, Sat Gupta
Format: Article
Language:English
Published: Instituto Nacional de Estatística | Statistics Portugal 2019-10-01
Series:Revstat Statistical Journal
Subjects:
Online Access:https://revstat.ine.pt/index.php/REVSTAT/article/view/280
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author Shakeel Ahmed
Javid Shabbir
Sat Gupta
author_facet Shakeel Ahmed
Javid Shabbir
Sat Gupta
author_sort Shakeel Ahmed
collection DOAJ
description The article presents predictive estimation of population mean of the study variable in Ranked Set Sampling (RSS). It is shown that the predictive estimators in RSS using mean per unit estimator, ratio estimator and regression estimator as predictor for non-sampled values are equivalent to the corresponding classical estimators in RSS. On the other hand, when product estimator is used as predictor, the resulting estimator differs from the classical product estimator under RSS. Expressions for the Bias and the Mean Squared Error (MSE) of the proposed estimators are obtained up to first order of approximation. A simulation study is conducted to observe the performance of estimators under predictive approach.
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spelling doaj.art-97f72cb199dd46e6ab10ad9729205b692022-12-22T04:02:45ZengInstituto Nacional de Estatística | Statistics PortugalRevstat Statistical Journal1645-67262183-03712019-10-0117410.57805/revstat.v17i4.280Predictive Estimation of Population Mean in Ranked Set SamplingShakeel Ahmed 0Javid Shabbir 1Sat Gupta 2Quaid-i-Azam UniversityQuaid-i-Azam UniversityUniversity of North Carolina at Greensboro The article presents predictive estimation of population mean of the study variable in Ranked Set Sampling (RSS). It is shown that the predictive estimators in RSS using mean per unit estimator, ratio estimator and regression estimator as predictor for non-sampled values are equivalent to the corresponding classical estimators in RSS. On the other hand, when product estimator is used as predictor, the resulting estimator differs from the classical product estimator under RSS. Expressions for the Bias and the Mean Squared Error (MSE) of the proposed estimators are obtained up to first order of approximation. A simulation study is conducted to observe the performance of estimators under predictive approach. https://revstat.ine.pt/index.php/REVSTAT/article/view/280efficiencyproduct estimatorratio estimatorregression estimatorRSS
spellingShingle Shakeel Ahmed
Javid Shabbir
Sat Gupta
Predictive Estimation of Population Mean in Ranked Set Sampling
Revstat Statistical Journal
efficiency
product estimator
ratio estimator
regression estimator
RSS
title Predictive Estimation of Population Mean in Ranked Set Sampling
title_full Predictive Estimation of Population Mean in Ranked Set Sampling
title_fullStr Predictive Estimation of Population Mean in Ranked Set Sampling
title_full_unstemmed Predictive Estimation of Population Mean in Ranked Set Sampling
title_short Predictive Estimation of Population Mean in Ranked Set Sampling
title_sort predictive estimation of population mean in ranked set sampling
topic efficiency
product estimator
ratio estimator
regression estimator
RSS
url https://revstat.ine.pt/index.php/REVSTAT/article/view/280
work_keys_str_mv AT shakeelahmed predictiveestimationofpopulationmeaninrankedsetsampling
AT javidshabbir predictiveestimationofpopulationmeaninrankedsetsampling
AT satgupta predictiveestimationofpopulationmeaninrankedsetsampling