Title:
A Bivariate Teissier Distribution: Properties, Bayes Estimation and Application

dc.contributor.authorVikas Kumar Sharma
dc.contributor.authorSudhanshu Vikram Singh
dc.contributor.authorAshok Kumar Pathak
dc.date.accessioned2026-02-09T04:34:13Z
dc.date.issued2024
dc.description.abstractThis article presents a bivariate extension of the Teissier distribution, whose univariate marginal distributions belong to the exponentiated Teissier family. Analytic expressions for the different statistical quantities such as conditional distribution, joint moments, and quantile function are explicitly derived. For the proposed distribution, the concepts of reliability and dependence measures are also explored in details. Both the maximum likelihood technique and the Bayesian approach are utilised in the process of parameter estimation for the proposed distribution with unknown parameters. Several numerical experiments are reported to study the performance of the classical and Bayes estimators for varying sample size. Finally, a bivariate data is fitted using the proposed distribution to show its applicability over the bivariate exponential, Rayleigh, and linear exponential distributions in real-life situations. © Indian Statistical Institute 2023.
dc.identifier.doi10.1007/s13171-023-00314-w
dc.identifier.issn0976836X
dc.identifier.urihttps://doi.org/10.1007/s13171-023-00314-w
dc.identifier.urihttps://dl.bhu.ac.in/bhuir/handle/123456789/48559
dc.publisherSpringer
dc.subject62F15
dc.subjectBayes estimator
dc.subjectBivariate distribution
dc.subjectMaximum likelihood estimator
dc.subjectMean residual life
dc.subjectMeasures of dependence
dc.subjectPrimary 62H05
dc.subjectQuantile function
dc.subjectSecondary 62H12
dc.subjectTeissier distribution
dc.titleA Bivariate Teissier Distribution: Properties, Bayes Estimation and Application
dc.typePublication
dspace.entity.typeArticle

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