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What is Reliability Estimation in Multicomponent Systems about?

This thesis presents methods for estimating the reliability of a multicomponent system using progressively censored data from Chen distributions. It develops classical, Bayesian, and generalized estimation techniques, including maximum likelihood estimators and Markov Chain Monte Carlo methods, and provides a simulation study alongside real-world data analysis. The research evaluates the performance of these estimators in terms of bias, confidence intervals, and testing power.

Author

drem land

Language

EN