A confluent hypergeometric generalized inverse Gaussian distribution

A new generalized extended inverse gaussian density function involving a confluent hypergeometric function is defined. closed form representations of a generalized extended inverse gaussian density function and the corresponding moment generating function are provided in terms of meijer’s g-function. some other statistical functions which are associated with the proposed distribution are also derived. many distributions can be obtained as limiting cases of the proposed density function. this density is utilized to model an actual data set. the new distribution provides a better fit than related distributions as measured by the anderson-darling and cramér-von mises statistics. the proposed distribution could,for instance,find applications in the physical and biological sciences and in particular be helpful to researchers working in special functions as well as reliability analysis,survival models and diffraction theory. © 2015 pakistan journal of statistics.