Simultaneous confidence intervals for all differences of coefficients of variation of log-normal distributions

Novel approaches were proposed for constructing simultaneous confidence intervals for all differences of coefficients of variation of log-normal distributions, using the method of variance estimates recovery insert ignore into journalissuearticles values(MOVER); approach and the computational approach. They are then compared with the fiducial generalized confidence interval insert ignore into journalissuearticles values(FGCI); approach which was presented by insert ignore into journalissuearticles values(W. Thangjai, S. Niwitpong and S. Niwitpong, Simultaneous fiducial generalized confidence intervals for all differences of coefficients of variation of log-normal distributions, Lecture Notes in Artificial Intelligence, 2016);. A Monte Carlo simulation was conducted to compare the performances of these simultaneous confidence intervals based on the coverage probability and average length. Simulation results show that the MOVER approach is satisfactory performances for all sample case insert ignore into journalissuearticles values($k$); and sample size insert ignore into journalissuearticles values($n$);. Moreover, the computational approach performs as well as the MOVER approach when the sample size is large. Our approaches are applied to an analysis of a real data set from rainfall in regions of Thailand.