New Approximate Bayesian Confidence Intervals for the Coefficient of Variation of a Gaussian Distribution

Authors

Vincent A. R. Camara, Research Center for Bayesian Applications, Inc., Largo, FLFollow

Abstract

Confidence intervals are constructed for the coefficient of variation of a Gaussian distribution. Considering the square error and the Higgins-Tsokos loss functions, approximate Bayesian models are derived and compared to a published classical model. The models are shown to have great coverage accuracy. The classical model does not always yield the best confidence intervals; the proposed models often perform better.

DOI

10.22237/jmasm/1335845520