Sharma V.K.Singh S.V.Pathak A.K.2025-01-132025-01-1320240976836Xhttps://dl.bhu.ac.in/ir/handle/123456789/2490This 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.en62F15Bayes estimatorBivariate distributionMaximum likelihood estimatorMean residual lifeMeasures of dependencePrimary 62H05Quantile functionSecondary 62H12Teissier distributionArticle10.1007/s13171-023-00314-w