Reliability Estimation in Lindley Populations Using Hybrid Censored Data
Abstract
The
main focus of the study is to make inferences on the stress-strength
reliability (SSR) for Lindley distributions utilizing hybrid censored data,
where and respectively are the
strength and stress variables which follow distinct Lindley distributions. For
SSR, the asymptotic confidence intervals are constructed along with the maximum
likelihood estimates. Under a linear exponential (Linex) loss function, the
Bayes estimator of SSR is calculated while taking into account non-informative
and gamma informative priors The Bayes estimators are derived using the
Tierney-Kadane’s approximation and Markov Chain Monte Carlo (MCMC) techniques.
Also, the MCMC method-based HPD credible interval for SSR is developed. A Monte
Carlo numerical research is conducted to compare various estimators and
censoring techniques. Finally, a real-world example is examined for explanatory
purposes
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