Abstract

Instances of the Meijer G function may be used as representations for the probability density function (p.d.f.) and cumulative density function (c.d.f.) of several distributions. However, although the Meijer G function is a very handy representation for the p.d.f. and c.d.f. of these distributions, and nevertheless prominent progress has been made in its computation, this still remains very heavy, and time consuming, even with the newer versions of symbolic and extended precision softwares, so that the development of sharp and fast approximations is a desirable goal. In this paper it is shown how extremely sharp approximations for particular instances of the Meijer G function may be based on the probability density and cumulative distribution functions of the Generalized Near-Integer Gamma distribution.

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