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BAYESIAN ESTIMATION FOR THE PARAMETERS OF POISSON-LOMAX DISTRIBUTION USING CONDITIONAL AND UNCONDITIONAL GAMMA PRIORS
Journal article

BAYESIAN ESTIMATION FOR THE PARAMETERS OF POISSON-LOMAX DISTRIBUTION USING CONDITIONAL AND UNCONDITIONAL GAMMA PRIORS

Saman Hanif Shahbaz, Saeed Al-Ghamdi, Khushnoor Khan and Muhammad Qaiser Shahbaz
Advances and applications in statistics, Vol.51(1), pp.1-15
17/08/2017
DOI: https://doi.org/10.17654/AS051010001

Abstract

Mathematics Physical Sciences Science & Technology Statistics & Probability
In this paper, we have performed Bayesian estimation of parameters of Poisson-Lomax distribution. The estimation has been done by using gamma priors under two situations, namely, unconditional and conditional priors. We have performed MCMC study under Metropolis-Hasting algorithm to estimate the parameters numerically. The estimation has been done under squared error and MLINEX loss functions.

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