Exponentiated Power Half Logistic Distribution: Theory and Applications

Abstract

The frequent occurrence of data that may not be adequately modeled using any of the existing distributions has led to the continual introduction of new distributions. One way of introducing a new distribution is to generalize an existing distribution. Among the methods of generalizing distributions, the power transformation and exponential techniques have gained wide acceptability because of their tendency to generate highly flexible distributions. A new distribution called the exponentiated power half logistic distribution is presented in this paper. We establish
the relationships between the distribution and some well-known distributions. Raw moment, moment generating function, entropy and order statistics corresponding to the new distribution are discussed. Real life applications of the distribution are also considered. The goodness of fits of the new distribution to three real data sets is compared with that of each of power half logistic distribution, exponentiated half logistic distribution and half logistic distribution using some goodness of fit statistics. The results obtained show that the new model fits each of the data better than the other models.