EXPONENTIATED GENERALIZED EXPONENTIATED LOMAX DISTRIBUTION

Abstract

Studies on probability distribution functions and their properties are needful as they are very important in modeling random phenomena. However, research has shown that some real life data can be modeled more adequately using distributions derived by combining or mixing known related distributions. Exponentiated Generalized Exponentiated Lomax (EGEL) distribution that contains five parameters was developed from compounding exponentiated generalized family and exponentiated lomax distribution. The probability density function and cumulative distribution functions are studied and various structural properties of the developed distribution were derived such as the survival function, hazard function, reversed hazard function, odds function, renyi entropy, asymptotic and order statistics. The estimation of the model parameters were performed using maximum likelihood method. The simulation studies was carried out and application of the model to real life data was done to assess the efficiency and consistency of the developed model, the result shows that the developed distribution perform better than other existing related generalized distribution.