A simulation based approach to the parameter estimation for the three-parameter gamma distribution

Authors

Wan Kai Pang, The Hong Kong Polytechnic University
Shui Hung Hou, The Hong Kong Polytechnic University
Bosco W.T. Yu, The Hong Kong Polytechnic University
Wing Kin Ken Li, Hong Kong Institute of Vocational Education (Tsing Yi), Vocational Training CouncilFollow

Document Type

Journal Article

Publication Date

2004

Keywords

Gamma distribution, Continuation method, Markov chain Monte Carlo, Adaptive rejection sampling

DOI

10.1016/S0377-2217(02)00883-4

Abstract

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.

Source Publication

European Journal of Operational Research

Volume Number

155

Issue Number

3

ISSN

0377-2217

First Page

675

Last Page

682

Recommended Citation

Pang, W.,Hou, S.,Yu, B.,& Li, W. (2004). A simulation based approach to the parameter estimation for the three-parameter gamma distribution. European Journal of Operational Research, 155 (3), 675-682. http://dx.doi.org/10.1016/S0377-2217(02)00883-4