The stable distribution, in its many parametrizations, is central to many stochastic processes. Many random variables that occur in the study of Lévy processes are related to it. Good progress has been made recently for simulating various quantities related to the stable law. In this note, we...

An efficient Monte Carlo method for random sample generation from high dimensional distributions of complex structures is developed. The method is based on random discretization of the sample space and direct inversion of the discretized cumulative distribution function. It requires only the...

We present a black-box style rejection method that is valid for generating random variables with any log-concave density, provided that one knows a mode of the density. When the density is only known up to a constant factor, that method is no longer applicable.

There exists a vast literature on nonuniform random variate generators. Most of these generators are especially designed for a particular distribution. However, in pratice only a few of these are available to practioners. Moreover, for problems as (e.g.) sampling from the truncated normal...