The question of how to describe non-normal distributions is a statistical problem with deep historical roots. A powerful graphical tool for detecting non-normality of a random variable
\(X\) is the normal probability plot. Its natural generalization consists in writing
\(X\) as a function of a unit Gaussian variable
\(Z\). The Cornish-Fisher expansion is of this type, as are John W. Tukey's
\(g-h\)-transformations. We will explain these methods and discuss some applications.
Les transparents seront en anglais et la conférence sera donnée en français.