Confidence Intervals for Coefficient of Variation of Inverse Gaussian Distribution

Abstract

The coefficient of variation is an useful indicator to measure and compare separated data in different units. This paper proposes the new confidence interval for the single coefficient of variation and the difference between coefficients of variation of Inverse Gaussian distribution using the generalized confidence interval (GCI) and the bootstrap percentile confidence interval. A Monte Carlo simulation is used to construct and compare the performance of these confidence intervals based on the coverage probability and average length. The results of the simulation study showed that the GCI is an appropriate method to construct the confidence interval for the single coefficient of variation and the difference between coefficients of variation. The proposed approaches are illustrated based on the real data.