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Noninformative priors for the generalized half-normal distribution
Institution:1. Department of Computer and Data Information, Sangji University, Wonju, 220-702, Republic of Korea;2. Department of Statistics, Sungkyunkwan University, Seoul, 110-745, Republic of Korea;3. Department of Asset Management, Daegu Haany University, Kyungsan, 712-240, Republic of Korea
Abstract:In this paper, we develop noninformative priors for the generalized half-normal distribution when scale and shape parameters are of interest, respectively. Especially, we develop the first and second order matching priors for both parameters. For the shape parameter, we reveal that the second order matching prior is a highest posterior density (HPD) matching prior and a cumulative distribution function (CDF) matching prior. In addition, it matches the alternative coverage probabilities up to the second order. For the scale parameter, we reveal that the second order matching prior is neither a HPD matching prior nor a CDF matching prior. Also, it does not match the alternative coverage probabilities up to the second order. For both parameters, we present that the one-at-a-time reference prior is a second order matching prior. However, Jeffreys’ prior is neither a first nor a second order matching prior. Methods are illustrated with both a simulation study and a real data set.
Keywords:Generalized half-normal distribution  Matching prior  Reference prior
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