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Sharp Error Bounds for Asymptotic Expansions of the Distribution Functions for Scale Mixtures
Authors:Ryoichi Shimizu  Yasunori Fujikoshi
Institution:(1) The Institute of Statistical Mathematics, 4-6-7 Minami-Azabu, Minato-ku, Tokyo, 106, Japan;(2) Department of Mathematics, Hiroshima University, Kagamiyama 1-3-1, Higashi-Hiroshima, Hiroshima, 739, Japan
Abstract:Let Z be a random variable with the distribution function G(x) and let s be a positive random variable independent of Z. The distribution function F(x) of the scale mixture X = sZ is expanded around G(x) and the difference between F(x) and its expansion is evaluated in terms of a quantity depending only on G and the moments of the powers of the variable of the form sdelta/gr - 1, where rgr(> 0) and delta(= ±1) are parameters indicating the types of expansion. For delta = -1, the bound is sharp under some extra conditions. Sharp bounds for errors of the approximations of the scale mixture of the standard normal and some gamma distributions are given either by analysis (delta = -1) or by numerical computation (delta = 1).
Keywords:Asymptotic expansion  normal distribution  gamma distribution  scale mixture  sharp bound
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