A Bivariate Teissier Distribution: Properties, Bayes Estimation and Application

Vikas Kumar Sharma (), Sudhanshu Vikram Singh and Ashok Kumar Pathak
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Vikas Kumar Sharma: Banaras Hindu University
Sudhanshu Vikram Singh: Institute of Infrastructure Techonology Research And Management
Ashok Kumar Pathak: Central University of Panjab

Sankhya A: The Indian Journal of Statistics, 2024, vol. 86, issue 1, No 3, 67-92

Abstract: Abstract This 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.

Keywords: Teissier distribution; Bivariate distribution; Measures of dependence; Mean residual life; Quantile function; Maximum likelihood estimator; Bayes estimator; Primary 62H05; Secondary 62H12; 62F15 (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s13171-023-00314-w

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