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. Keyword: Extended Lomax distribution, Markov chain Monte Carlo (MCMC), Bayesian estimation, OpenBUGS.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: International Journal of Mathematics Trends and Technology
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
