Statistical Inference on the Ratio of Delta-Lognormal Coefficients of Variation

  • Noppadon Yosboonruang Department of Applied Statistics, Faculty of Applied Science, King Mongkut’s University of Technology North Bangkok, Bangkok, Thailand
  • Suparat Niwitpong Department of Applied Statistics, Faculty of Applied Science, King Mongkut’s University of Technology North Bangkok, Bangkok, Thailand
Keywords: Generalized confidence interval, Method of variance estimates recovery, Variance stabilizing transformation, Wilson score method, Jeffreys method, Rainfall

Abstract

The coefficient of variation is useful to measure and compare the dispersion of the data when different units are used in different datasets. This article aims to propose new confidence intervals for the ratio of two independent coefficients of variation with delta-lognormal distribution. The proposed methods include the concept of the generalized confidence interval and the method of variance estimate recovery. They are applied with three methods, variance stabilizing transformation, Wilson score method, and Jeffreys method. The performance of the confidence intervals was assessed by the coverage probabilities and the expected lengths via the Monte Carlo simulation. The outcomes of the simulation study showed that the generalized confidence interval is appropriate to construct the confidence interval for the ratio of delta-lognormal coefficients of variation. Two rainfall datasets from Nakhon Ratchasima, Thailand are used to demonstrate the proposed confidence intervals.

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Published
2021-07-13
Section
Research Articles