International Journal of Mathematics and Mathematical Sciences
Volume 2003 (2003), Issue 9, Pages 587-592
doi:10.1155/S0161171203207237
Abstract
We give a new characterization of inverse Gaussian distributions
using the regression of a suitable statistic based on a given
random sample. A corollary of this result is a characterization
of inverse Gaussian distribution based on a conditional joint
density function of the sample. Application of this corollary as
a transformation in the procedure to construct EDF (empirical
distribution function) goodness-of-fit tests for inverse Gaussian
distributions is also studied.