A New Test for the Homogeneity of Inverse Gaussian Scale Parameters Based on Computational Approach Test

Abstract

In this paper, we focused on testing homogeneity of scale parameters of k Inverse Gaussian distributions (IGDs) since this distribution is one of the most common distribution for analyzing nonnegative right-skewed data. We have proposed a new test statistic based on the Computational Approach Test (CAT), which is a type of parametric bootstrap method, for testing homogeneity of scale parameters of k IGDs. Simulation results have been presented to compare the performances of the proposed method and existing methods such as the likelihood ratio test, modified likelihood ratio test and generalized likelihood ratio test in terms of type I error rate and power. The results showed that the proposed CAT is better than the others in terms of the type I error rates and powers in some cases.