Reliability analysis of the Stress-Strength model from truncated Pareto distribution based on progressive Type-II censored samples.

Abstract

In this project, we studied the stress strength reliability (SSR) models. The stress-strength model has many applications in engineering problems, for example the strength of a building being subjected to earthquake, the strength of a rocket motor being greater than its working pressure, and the strength of a bridge. We estimated the reliability parameter using maximum likelihood estimation method in three cases (arbitrary case, common truncated case, and common resilience parameter case). We computed the maximum likelihood estimator (MLE) of the reliability parameter R and studied the properties of the estimator of the parameter R using a great amount of simulation studies and illustrate our method through some real data examples. Moreover, we compute the generalized confidence intervals passed on pivotal quantities. We computed the bootstrap confidence intervals. We found that, the confidence interval is wider in the arbitrary parameter case, and that there is no large difference between the estimators of reliability parameter using different methods.