The main objective of this paper is to develop the Bayesian analysis for Constant Stress
Accelerated Life Test (CSALT) under time censoring scheme of the Generalized Logistic
(GL) Failure times. The power law function is used to represent the relationship between
the stress and the scale parameters of a test unit. Bayes estimates are obtained using
Markov Chain Monte Carlo (MCMC), simulation algorithm based on Gibbs sampling.
Then, Monte Carlo error (MC error), credible intervals, and predicted values of the two
scale parameters and the reliability function under design stress are obtained. Numerical
illustration is addressed for illustrating the theoretical results. Win-Bugs software package
is used for implementing Markov Chain Monte Carlo (MCMC) simulation and Gibbs
sampling.
Accelerated Life Test; Constant Stress; Time Censoring; Power Law Function, Bayesian Method; Generalized Logistic Distribution; Markov Chain Monte Carlo; Gibbs Samples, Win-Bugs.