Statistical Analysis of Inverse Lindley Data Using Adaptive Type-II Progressively Hybrid Censoring with Applications

This paper deals with the statistical inference of unknown parameter and some life parameters inverse Lindley distribution under assumption that data are adaptive Type-II progressively censored. The maximum likelihood method is considered to acquire point interval estimates parameter, reliability, hazard rate functions. approximate confidence intervals also addressed. delta taken into consideration variances estimators reliability functions get required intervals. Based on gamma prior, we further consider Bayesian estimation different parameters. Bayes obtained by considering squared error general entropy loss highest posterior density credible employing Markov chain Monte Carlo procedure. An exhaustive numerical study conducted compare offered regard their root means error, relative absolute biases, lengths, coverage probabilities. To explain suggested methods, two applications investigated. findings show perform better than those based method. estimations using asymmetric function give more efficient symmetric loss. Finally, recommended be used as a suitable model fit airborne communication transceiver wooden toys sets when compared competitive models including Weibull, alpha power inverted exponential.