Estimating the Population Coefficient of Variation by Confidence Intervals

DOI10.1080/03610918.2011.568151zbMath1271.62050OpenAlexW2120581632MaRDI QIDQ3102875

B. M. Golam Kibria, Shipra Banik

Publication date: 25 November 2011

Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610918.2011.568151

zbMATH Keywords

skewed distributionscoverage probabilitysimulation studybootstrap methods

Mathematics Subject Classification ID

Related Items (12)

A new asymptotic distribution-based method for testing the signal-to-noise ratio in birth weight data from Thailand ⋮ On Symmetrizing Transformation of the Sample Coefficient of Variation from a Normal Population ⋮ Nonparametric Tests for Comparing Several Coefficients of Variation ⋮ Bootstrap confidence intervals for the coefficient of quartile variation ⋮ Unnamed Item ⋮ Confidence intervals for mean and difference of means of normal distributions with unknown coefficients of variation ⋮ Multivariate coefficients of variation: comparison and influence functions ⋮ Symmetrizing and variance stabilizing transformations of sample coefficient of variation from inverse Gaussian distribution ⋮ Estimation of the coefficient of variation for non-normal model using progressive first-failure-censoring data ⋮ Confidence intervals for the weighted coefficients of variation of two-parameter exponential distributions ⋮ Small-sample tests for the equality of two normal cumulative probabilities, coefficients of variation, and Sharpe ratios ⋮ Estimation and testing of a common coefficient of variation from inverse Gaussian distributions

Cites Work

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• Distribution of the Coefficient of Variation and the Extended "t" Distribution
• Tests of Coefficients of Variation of Normal Population
• A Nonparametric Bootstrap Test for the Equality of Coefficients of Variation
• Nonparametric confidence intervals for the one- and two-sample problems
• Confidence intervals for the coefficient of variation for the normal and log normal distributions
• The Sampling Distribution of the Coefficient of Variation

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