Posterior analysis of weighted erlang distribution
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CitationHincal, E. ve Alsaadi, S. (2019). Posterior analysis of weighted erlang distribution. International Conference of Mathematical Sciences (ICMS 2019). s. 130.
Erlang distribution is continuous probability distribution that has application in several field such as stochastic process and mathematical biology, due to its relation with exponential and gamma distribution. In the sense that, the duration of the successive calls follows the Erlang distribution, if individual telephone calls is exponentially distributed to the time period. In this study, Bayesian estimation is employed in the estimation of scale parameter od weighted Erlang distribution. The posterior distribution is derived under two informative priors, which are inverse exponential and inverse chi square prior. The Bayes estimated and their relative posterior risks are derived under the assumption of squared error loss function, and precautionary loss function. A Monte Carlo simulation is carried out in order to obtain the numerical value of the estimates. It was observed that squared error loss function performs best when inverse exponential prior is used. Keywords: Erlang distribution, Bayesian estimation, loss function.
SourceInternational Conference of Mathematical Sciences (ICMS 2019)
- Makale Koleksiyonu 
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