Bayesian Analysis of Extended Lomax
Distribution

Shankar Kumar Shrestha; Vijay Kumar

doi:https://doi.org/10.14445/22315373/IJMTT-V7P505

International Journal of Mathematics Trends and Technology

Research Article | Open Access | Download PDF

Volume 7 | Number 1 | Year 2014 | Article Id. IJMTT-V7P505 | DOI : https://doi.org/10.14445/22315373/IJMTT-V7P505

Bayesian Analysis of Extended Lomax Distribution

Shankar Kumar Shrestha , Vijay Kumar

Abstract

In this paper, the Markov chain Monte Carlo (MCMC) method is used to estimate the parameters of Extended Lomax distribution, based on a complete sample. The proposed methodology can be used to obtain the Bayes estimates the parametric function such as reliability function, hazard function, etc under different loss functions and is also suitable for empirical modeling. A real data set is considered for illustration under non-informative and informative set of priors.

Keywords

Extended Lomax distribution, Markov chain Monte Carlo (MCMC), Bayesian estimation, OpenBUGS.

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Citation :

Shankar Kumar Shrestha , Vijay Kumar, "Bayesian Analysis of Extended Lomax Distribution," International Journal of Mathematics Trends and Technology (IJMTT), vol. 7, no. 1, pp. 33-41, 2014. Crossref, https://doi.org/10.14445/22315373/IJMTT-V7P505