Abstract
The inverse Gaussian distribution provides a flexible model for analyzing positive, right-skewed data. The generalized variable test for equality of several inverse Gaussian means with unknown and arbitrary variances has satisfactory Type-I error rate when the number of samples (k) is small (Tian, 2006). However, the Type-I error rate tends to be inflated when k goes up. In this article, we propose a parametric bootstrap (PB) approach for this problem. Simulation results show that the proposed test performs very satisfactorily regardless of the number of samples and sample sizes. This method is illustrated by an example.
Notes
PB* PB-test proposed in this article GV* generalized variable approach (Tian, 2006)
PB* PB-test proposed in this article GV* generalized variable approach (Tian, 2006)
PB* PB-test proposed in this article GV* generalized variable approach (Tian, 2006)