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    Asymptotic Sampling Distribution of Inverse Coefficient of Variation and its Applications: Revisited

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    Date
    2014
    Author
    Albatineh, Ahmad
    Kibria, Golam
    Zogheib, Bashar
    Type
    Journal Article
    Peer-Reviewed
    Metadata
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    Abstract
    Sharma and Krishna (1994) derived mathematically an appealing asymptotic confidence interval for the population signal-to-noise ratio (SNR). In this paper, an evaluation of the performance of this interval using monte carlo simulations using randomly generated data from normal, log-normal, $\chi^2$, Gamma, and Weibull distributions three of which are discussed in Sharma and Krishna (1994). Simulations revealed that its performance, as measured by coverage probability, is totally dependent on the amount of noise introduced. A proposal for using ranked set sampling (RSS) instead of simple random sampling (SRS) improved its performance. It is recommended against using this confidence interval for data from a log-normal distribution. Moreover, this interval performs poorly in all other distributions unless the SNR is around one.
    URI
    http://hdl.handle.net/11675/837
    External link
    https://sciencepubco.com/index.php/IJASP/article/view/1475
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