Statistical Inference for the Chen Distribution Based on Upper Record Values

This article presents the Bayesian and classical inferences for the Chen distribution assuming upper record values. As the posterior distribution is not in a closed form, a Markov Chain Monte Carlo method is presented to obtain the posterior summaries. To assess the effect of prior on the estimated parameters, sensitivity analysis is also a part of this study. Moreover, a comparison between the Bayesian and frequentist approaches is also given. Besides the simulation studies, a real data example to show the application of the study is also discussed. © 2019, Springer-Verlag GmbH Germany, part of Springer Nature.