Title:
A new asymmetric loss function for estimation of any parameter

dc.contributor.authorDinesh Kumar
dc.contributor.authorPawan Kumar
dc.contributor.authorPradip Kumar
dc.contributor.authorUmesh Singh
dc.contributor.authorPrashant Kumar Chaurasia
dc.date.accessioned2026-02-07T09:18:43Z
dc.date.issued2020
dc.description.abstractA new asymmetric loss function which is suitable for estimation of location as well as scale and other parameters has been introduced. To check the superiority of the proposed loss function over some existing and exploited loss functions such as squared error loss function (SELF), general entropy loss function (GELF), LINEX loss function and Logarithmic-SELF (LSELF), we have calculated the Bayes estimators of the parameterθ of exponential distribution under SELF, GELF, LINEX loss function, Logarithmic- SELF (LSELF) and the proposed exponential squared error loss function (ESELF) for complete sample from the exponential distribution. A data set has been considered to show its application to the real problems. The simulation study is carried out to compare the performance of Bayes estimators in terms of their posterior risks. © 2020 DAV College. All rights reserved.
dc.identifier.issn9731903
dc.identifier.urihttps://dl.bhu.ac.in/bhuir/handle/123456789/34748
dc.publisherDAV College
dc.subjectBayes estimator
dc.subjectExponential distribution
dc.subjectLoss function
dc.subjectPosterior risks
dc.subjectSimulation study
dc.titleA new asymmetric loss function for estimation of any parameter
dc.typePublication
dspace.entity.typeArticle

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