Résumé: We consider the problem of the exact simulation of random variables Z that satisfy the distributional identity Z L= VY + (1 . V)Z, where V ?¸ [0, 1] and Y are independent, and L= denotes equality in distribution. Equivalently, Zis the limit of a Markov chain driven by that map.We give an algorithm that can be automated under the condition that we have a source capable of generating independent copies of Y, and that V has a density that can be evaluated in a black-box format. The method uses a doubling trick for inducing coalescence in coupling from the past. Applications include exact samplers for many Dirichlet means, some two-parameter Poisson.Dirichlet means, and a host of other distributions related to occupation times of Bessel bridges that can be described by stochastic fixed point equations.

Langue: Anglais