Double Inverse-Gaussian Distributions and Associated Inference

In order to have more flexibility, several double distributions have been studied in the literature. In this paper, we propose a double inverse Gaussian distribution using random sign mixture transform and study its associated inferences. The maximum likelihood estimation is performed to estimate the parameters. Extensive simulation studies are carried out to examine the performance of the estimators and the corresponding confidence intervals of the parameters. A real data set example is presented to illustrate the procedure.