Data analysis with applications in physics and engineering using XLindley model with improved adaptive Type-II progressively censored samples.

ABSTRACT: Recently, a novel improved adaptive Type-II progressive censoring strategy has been suggested in order to obtain adequate data from trials that require a lengthy amount of time. Considering this scheme, this paper focuses on various classical and Bayesian estimation challenges for parameter and some reliability metrics for the XLindley distribution. Two classical estimation methods are considered from the classical perspective to get the point and interval estimations of the model parameter as well as reliability and hazard rate functions. In addition to the usual approaches, the Bayesian methodology is looked at by leveraging the squared error loss function and the Markov chain Monte Carlo technique. The Bayes point and credible intervals are obtained based on two forms of the posterior d

SUBMITTER: Alotaibi R 

PROVIDER: S-EPMC11295576 | biostudies-literature | 2024 Jul

REPOSITORIES: biostudies-literature