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Statistical inference on stress-strength reliability of cold standby systems using discrete phase type distribution
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DOI：10.1080/00949655.2026.2630233.png)
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Abstract
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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.
Keywords:
Reliability
cold standby
discrete phase type distribution
Bayesian inference
EM algorithm
Journal
J
IF:
1.2
Papers:
114
Citations:
4.1K
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