Confidence Intervals for the Coefficient of Variation in a Normal Distribution with a Known Mean and a Bounded Standard Deviation
The natural parameter space is known to be bounded in many real applications such as engineering, science and social science. The standard confidence interval derived from the classical Neyman procedure is unsatisfactory in the case of a bounded parameter space. New confidence intervals for the coefficient of variation in a normal distribution with a known population mean and a bounded standard deviation are proposed in this paper.
A simulation study has been conducted to compare the performance of the proposed confidence intervals.