Estimation functions and uniformly most powerful tests for inverse Gaussian distribution
The aim of this article is to develop estimation functions by confidence regions for the inverse Gaussian distribution with two parameters and to construct tests for hypotheses testing concerning the parameter when the mean parameter is known. The tests constructed are uniformly most powerful tests and for testing the point null hypothesis it is also unbiased.