The shifted exponential-G family of distributions : Properties and applications
Joseph Thomas Eghwerido, Friday Ikechukwu Agu, Olayemi Joshua Ibidoja
Abstract
This article introduces a new generator called the shifted exponential-G (SHE-G) generator for generating continuous distributions. The proposed model extends the existing shifted exponential and the exponential family of distributions. Some special models of the proposed model are presented. The density, hazard rate function and survival rate function of the SHE-G distribution are investigated and examined. The parameters of the SHE-G distribution are obtained by maximum likelihood method. The Bernstein method of generating the SHE-G model was also examined. A two bivariate approach for the proposed model was considered. A simulation was used to examine the performance of the estimators. A three real life data was employed to examine the goodness-of-fit test statistics of the empirical flexibility. The results of the test statistics show that the SHE-G distribution provides a better goodness-of-fit.