Group for Research in Decision Analysis

Modéliser la forme d'une distribution

Stephan Morgenthaler

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.