The long-term exponentiated complementary exponential geometric distribution under a latent complementary causes framework

Abstract

A new lifetime distribution which accommodates decreasing and unimodal hazard function is proposed in this paper. It is derived from the exponentiated complementary exponential geometric distribution and has it genesis on the compounding the exponential and geometric distributions. It can be used on a latent complementary causes scenario, where onle thethe minimum lifetime among all causes is observed. We derive the density, quantile, survival and failure rate functions for the proposed distribution, as well as some proprieties such as the characteristic function, mean, variance and r-th order statistics. The estimation is based on maximum likelihood approach. A simulation study performed in order to assess the performance of the maximum likelihood estimates of the parameters of the proposed distribution. The methodology is illustrated in three real datasets.