Publication:
A Comparative Study on Calibration Approach Based Estimators for Domain Estimation Utilizing Power Function: Revisited

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dc.contributor.authorAshutosh
dc.contributor.authorRai, Piyush Kant
dc.contributor.authorSingh, Ajeet Kumar
dc.date.accessioned2025-01-28T09:30:23Z
dc.date.available2025-01-28T09:30:23Z
dc.date.issued2023
dc.description.abstractThe calibration approach based estimators of the domain mean have growing demand during past couple of decades. Estimation of domains is another challenging task for surveyors and several efforts have been made to produce the reliable estimators for this purpose. Prominently the power function based estimators in the sample surveys are having dual advantages for the selection and their application to produce an improved estimation at any stage in the terms of efficiency without much complexity. In the domain estimation utilization of the power function in the development of calibration based estimators are also very promising and provide considerable results. A simulation study has examined for the comparison of several calibration estimators along with the proposed estimator in terms of the absolute relative bias and simulated relative standard error. � 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.
dc.identifier.doihttps://doi.org/10.1007/s40745-021-00365-6
dc.identifier.issn21985804
dc.identifier.urihttps://dl.bhu.ac.in/ir/handle/123456789/21322
dc.language.isoen
dc.publisherSpringer Science and Business Media Deutschland GmbH
dc.subjectAbsolute relative bias
dc.subjectCalibration approach
dc.subjectDirect indirect methods of estimation
dc.subjectDomain estimation
dc.subjectSimulated relative standard error
dc.titleA Comparative Study on Calibration Approach Based Estimators for Domain Estimation Utilizing Power Function: Revisited
dc.typeReview
dspace.entity.typePublication
journal.titleAnnals of Data Science
journalvolume.identifier.volume10

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2023