Bayesian Analysis of Two-Parameter Exponentiated Log-logistic Distribution

Authors

  • Arun Kumar Chaudhary Nepal Commerce Campus, T.U.

DOI:

https://doi.org/10.3126/pravaha.v25i1.31864

Keywords:

Bayesian estimation, Two-parameter exponentiated Log-logistic distribution, Markov chain Monte Carlo, Gamma Prior

Abstract

In this paper, the parameters of the two-parameter exponentiated log-logistic distribution based on a complete sample are estimated using the Markov chain Monte Carlo (MCMC) method. In order to perform full Bayesian analysis of the two-parameter exponentiated log-logistic distribution, the procedures are developed using the MCMC simulation method in Open BUGS, established software. The researcher has obtained the Bayes estimates of the parameters and their probability intervals are presented. The researcher has also discussed the estimation of the reliability function. For illustration under independent gamma priors, the real data set is considered.

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Author Biography

Arun Kumar Chaudhary, Nepal Commerce Campus, T.U.

Associate Professor

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Published

2020-10-08

How to Cite

Chaudhary, A. K. (2020). Bayesian Analysis of Two-Parameter Exponentiated Log-logistic Distribution. Pravaha, 25(1), 1–12. https://doi.org/10.3126/pravaha.v25i1.31864

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Section

Articles