Modeling statistic distributions for nonparametric goodness-of-fit criteria for testing complex hypotheses with respect to the inverse Gaussian law

We give percentage point tables and statistic distribution models for non-parametric goodness-of-fit criteria for testing complex hypothesis with respect to the inverse Gaussian law in case of using maximal likelihood estimates.

Presented by the member of Editorial Board: B. G. Volik