Date of Award
Spring 5-1-2012
Degree Type
Thesis
Degree Name
Master of Science (MS)
Department
Mathematics and Statistics
First Advisor
Dr. Gengsheng Qin
Abstract
The coefficient of variation (CV) is a helpful quantity to describe the variation in evaluating results from different populations. There are many papers discussing methods of constructing confidence intervals for a single CV, such as exact method and approximation methods for CV when the underlying distribution is a normal distribution. However, the exact method is computationally cumbersome, and approximation methods can't be applied when the underlying distribution is unknown. In this thesis, we propose the generalized confidence interval for CV when the underlying distribution is normal and three empirical likelihood-based non-parametric intervals for CV when the underlying distribution is unknown. Simulation studies are conducted to compare the relative performances of these intervals based on the coverage probability and average interval length. Finally, the application of the proposed methods is demonstrated by using some real examples.
DOI
https://doi.org/10.57709/2785351
Recommended Citation
Liu, Shuang, "Confidence Interval Estimation for Coefficient of Variation." Thesis, Georgia State University, 2012.
doi: https://doi.org/10.57709/2785351