A goodness-of-fit test for generalized error distribution

The Generalized Error Distribution is a widespread flexible family of symmetric probability distribution. Thanks to its properties it is becoming more and more popular in many science fields therefore determining if a sample is drawn from a GED is an important issue that usually is pursued with a graphical approach. In this paper we present a new goodness-of-fit test for GED that shows good performances for detecting non GED distribution when the alternative distribution is either skewed or a mixture. A comparison between well known tests and this new procedure is performed through a simulation study. We have developed a function that performs the analysis described in this paper in the R environment. The computational time required to compute this procedure is negligible.