On a proper way to select population failure distribution and a stochastic optimization method in parameter estimation

On a proper way to select population failure distribution and a stochastic optimization method in parameter estimation

0.00 Avg rating0 Votes
Article ID: iaor20084768
Country: Netherlands
Volume: 177
Issue: 1
Start Page Number: 604
End Page Number: 611
Publication Date: Feb 2007
Journal: European Journal of Operational Research
Authors: , ,
Keywords: markov processes
Abstract:

It is widely accepted that the Weibull distribution plays an important role in reliability applications. The reliability of a product or a system is the probability that the product or the system will still function for a specified time period when operating under some confined conditions. Parameter estimation for the three parameter Weibull distribution has been studied by many researchers in the past. Maximum likelihood has traditionally been the main method of estimation for Weibull parameters along with other recently proposed hybrids of optimization methods. In this paper, we use a stochastic optimization method called the Markov Chain Monte Carlo (MCMC) to carry out the estimation. The method is extremely flexible and inference for any quantity of interest is easily obtained.

Reviews

Required fields are marked *. Your email address will not be published.