A Universal Generator for Discrete Log-Concave Distributions

Wolfgang Hörmann


We give an algorithm that can be used to sample from any discrete log-concave distribution (e.g. the binomial and hypergeometric distributions). It is based on rejection from a discrete dominating distribution that consists of parts of the geometric distribution. The algorithm is uniformly fast for all discrete log-concave distributions and not much slower than algorithms designed for a single distribution.

Mathematics Subject Classification: 65C10 (Random Number Generation), 68C25

Key Words: Random number generation, log-concave distributions, rejection method, simulation.

Download Preprint