Statistical inference on stress-strength reliability of cold standby systems using discrete phase type distribution
Abstract
In this paper, an innovative reliability model of the system level-cold standby system is developed. This model integrates discrete phase type (DPH) distributions into the estimation of stress-strength reliability (SSR). The SSR expression for the system is derived by utilizing probability analysis and calculation. The estimators for the SSR are theoretically deduced by the maximum likelihood estimation (MLE) and Bayesian inference. The maximum likelihood estimates are obtained using the Expectation-Maximization (EM) algorithm, while the Gibbs sampling (GS) method is employed for the Bayesian inference. The deviations between these estimates and the actual values are visually illustrated in numerical experiments.
Fields of Study & Subjects
Statistical Distribution Estimation and Applications
Reliability and Maintenance Optimization
Software Reliability and Analysis Research
Publication details
- Journal / source
- Journal of Statistical Computation and Simulation
- Volume
- 96
- Issue
- 10
- Pages
- 2498–2529
- Publication date
- 2 March 2026
- Language
- EN