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Inferences on the Coefficients of Variation in a Multivariate Normal Population

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  • Ali Akbar Jafari

Abstract

In this article, the problem of testing the equality of coefficients of variation in a multivariate normal population is considered, and an asymptotic approach and a generalized p-value approach based on the concepts of generalized test variable are proposed. Monte Carlo simulation studies show that the proposed generalized p-value test has good empirical sizes, and it is better than the asymptotic approach. In addition, the problem of hypothesis testing and confidence interval for the common coefficient variation of a multivariate normal population are considered, and a generalized p-value and a generalized confidence interval are proposed. Using Monte Carlo simulation, we find that the coverage probabilities and expected lengths of this generalized confidence interval are satisfactory, and the empirical sizes of the generalized p-value are close to nominal level. We illustrate our approaches using a real data.

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  • Ali Akbar Jafari, 2015. "Inferences on the Coefficients of Variation in a Multivariate Normal Population," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 44(12), pages 2630-2643, June.
    • Handle: RePEc:taf:lstaxx:v:44:y:2015:i:12:p:2630-2643
    DOI: 10.1080/03610926.2013.788711
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    Cited by:

    1. Abbas Bahrampour & Zeynab Avazzadeh & Mohammad Reza Mahmoudi & António M. Lopes, 2022. "Improved Confidence Interval and Hypothesis Testing for the Ratio of the Coefficients of Variation of Two Uncorrelated Populations," Mathematics, MDPI, vol. 10(19), pages 1-15, September.
    2. Ali Akbar Jafari & Javad Shaabani, 2020. "Comparing scale parameters in several gamma distributions with known shapes," Computational Statistics, Springer, vol. 35(4), pages 1927-1950, December.

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