An automatic code generator for nonuniform random variate generation

  • Authors:

  • Josef Leydold;Gerhard Derflinger;Günter Tirler;Wolfgang Hörmann

  • Affiliations:

  • Department for Applied Statistics and Data Processing, University of Economics and Business Administration, Augasse 2-6, A-1090 Vienna, Austria;Department for Applied Statistics and Data Processing, University of Economics and Business Administration, Augasse 2-6, A-1090 Vienna, Austria;Department for Applied Statistics and Data Processing, University of Economics and Business Administration, Augasse 2-6, A-1090 Vienna, Austria;IE Department, Bogaziçi University Istanbul, 80815 Bebek-Istanbul, Turkey

  • Venue:
  • Mathematics and Computers in Simulation - Special issue: 3rd IMACS seminar on Monte Carlo methods - MCM 2001
  • Year:
  • 2003

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Abstract

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 distribution or sampling from fairly uncommon distributions there are often no algorithms available. In the last decade so called universal methods have been developed for these cases. The resulting algorithms are fast and have properties that make them attractive even for standard distributions.In this contribution we describe the concept of Automatic random variate generation where these methods are used to produce a single piece of code in a high level programming language. Using a web-based front-end to such a program this is an easy-to-use source for researchers and programmers for high quality generators for a large class of distributions. Using our UNURAN library we have implemented such a system, which is accessable at http://statistik.wu-wien.ac.at/anuran.