This paper aims to study the estimation of some unknown parameters of the Beta exponentiated Gompertz distribution under complete samples. The maximum likelihood and Bayes estimates of the three parameters are derived. Moreover, the Bayes estimators are studied under three different types of loss function such as; squared error, Linear-exponential, and general entropy loss functions. We used the importance sampling technique for computing the Bayes estimates. The performances of the estimates are compared through the mean square errors by Monte Carlo simulation study. In addition, comparisons are made between these estimators. Also, we rewrite the expansion of formula for its cumulative distribution and probability density functions. Survival, odds, hazard, cumulative hazard and reversed hazard functions are provided. Also, we obtained several properties of this distribution such as r ௧ non-central moment, moment generating function, incomplete and conditional moments, n ௧ moment of the residual and reversed residual life, inequality measures, and q – entropies. Finally, an application on real data-set are presented to determine whether the beta exponentiated Gompertz distribution is better than other well-known distributions for modeling the lifetime data sets.
Volume 11 | 02-Special Issue
Pages: 446-454