Generalized exponential Marshall-Olkin distribution

Abstract

The distribution of generalized exponential was invented by Rameshwar D. Gupta and Debasis Kundu in 2007. The distribution was the result of a generalized transformation of the exponential distribution. This paper explained the generalized exponential Marshall-Olkin distribution which is the result of the expansion of the generalized exponential distribution using the Marshall-Olkin method. The generalized exponential Marshall-Olkin distribution has a more flexible form than the previous distribution, especially in its hazard function which has various forms so that it can represent survival data better. The flexibility characteristic is due to the addition of new parameters to the generalized exponential Marshall-Olkin distribution. We explained some characteristics of the Marshall-Olkin generalized exponential distribution such as the probability density function (PDF), cumulative distribution function (CDF), survival function, hazard function, mean, and moments. Parameter estimation was conducted using the maximum likelihood method. In the application, it was shown data with generalized exponential Marshall-Olkin (GEMO) distribution. The GEMO distribution was modelled to the waiting time data until the damage to a lamp. The data was taken from Aarset data (1987). The results of modelling the waiting time data until the damage to a lamp on the distribution of GEMO and was compared to the distribution of alpha power Weibull. A comparison of models using Akaike information criteria (AIC) and Bayesian information criteria (BIC) shows that the distribution of GEMO is more suitable in modelling the lamp damage waiting time data than the distribution of alpha power Weibull.