Research Description
-is is an open access article distributed under the Creative Commons Attribution
License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is
properly cited.
Modelling data in applied areas particularly in reliability engineering is a prominent research topic. Statistical models play a vital
role in modelling reliability data and are useful for further decision-making policies. In this paper, we study a new class of
distributions with one additional shape parameter, called a new generalized exponential-X family. Some of its properties are taken
into account. -e maximum likelihood approach is adopted to obtain the estimates of the model parameters. For assessing the
performance of these estimators, a comprehensive Monte Carlo simulation study is carried out. -e usefulness of the proposed
family is demonstrated by means of a real-life application representing the failure times of electronic components. -e fitted
results show that the new generalized exponential-X family provides a close fit to data. Finally, considering the failure times data,
the Bayesian analysis and performance of Gibbs sampling are discussed. -e diagnostics measures such as the Raftery–Lewis,
Geweke, and Gelman–Rubin are applied to check the convergence of the algorithm.
