Confidence intervals for coefficients of variation in two-parameter exponential distributions

ABSTRACT

This article examines confidence intervals for the single coefficient of variation and the difference of coefficients of variation in the two-parameter exponential distributions, using the method of variance of estimates recovery (MOVER), the generalized confidence interval (GCI), and the asymptotic confidence interval (ACI). In simulation, the results indicate that coverage probabilities of the GCI maintain the nominal level in general. The MOVER performs well in terms of coverage probability when data only consist of positive values, but it has wider expected length. The coverage probabilities of the ACI satisfy the target for large sample sizes. We also illustrate our confidence intervals using a real-world example in the area of medical science.

KEYWORDS:

• Asymptotic confidence interval
• Generalized confidence interval
• Method of variance of estimates recovery
• Simulation
• Two-parameter exponential distribution

MATHEMATICS SUBJECT CLASSIFICATION:

• Primary 62F25
• Secondary 62F12

Acknowledgments

The authors are grateful to the associate editor and referees for the valuable comments and suggestions, which help to improve the quality of the article.

Funding

The authors are grateful to grant number KMUTNB-NRU-59-01 from King Mongkut’s University of Technology North Bangkok.