A simulation based approach to the parameter estimation for the three-parameter gamma distribution [An article from: European Journal of Operational Research]
Book Details
PublisherElsevier
ISBN / ASINB000RR0WA4
ISBN-13978B000RR0WA2
AvailabilityAvailable for download now
Sales Rank12,023,489
MarketplaceUnited States 🇺🇸
Description
This digital document is a journal article from European Journal of Operational Research, published by Elsevier in 2004. The article is delivered in HTML format and is available in your Amazon.com Media Library immediately after purchase. You can view it with any web browser.
Description:
The gamma distribution is one of the commonly used statistical distribution in reliability. While maximum likelihood has traditionally been the main method for estimation of gamma parameters, Hirose has proposed a continuation method to parameter estimation for the three-parameter gamma distribution. In this paper, we propose to apply Markov chain Monte Carlo techniques to carry out a Bayesian estimation procedure using Hirose's simulated data as well as two real data sets. The method is indeed flexible and inference for any quantity of interest is readily available.
Description:
The gamma distribution is one of the commonly used statistical distribution in reliability. While maximum likelihood has traditionally been the main method for estimation of gamma parameters, Hirose has proposed a continuation method to parameter estimation for the three-parameter gamma distribution. In this paper, we propose to apply Markov chain Monte Carlo techniques to carry out a Bayesian estimation procedure using Hirose's simulated data as well as two real data sets. The method is indeed flexible and inference for any quantity of interest is readily available.
