Black-Box Algorithms for Sampling from Continuous Distributions

Wolfgang Hörmann, Josef Leydold

Publikation: Working/Discussion PaperWU Working Paper

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For generating non-uniform random variates, black-box algorithms are powerful tools that allow drawing samples from large classes of distributions. We give an overview of the design principles of such methods and show that they have advantages compared to specialized algorithms even for standard distributions, e.g., the marginal generation times are fast and depend mainly on the chosen method and not on the distribution. Moreover these methods are suitable for specialized tasks like sampling from truncated distributions and variance reduction techniques. We also present a library called UNU.RAN that provides an interface to a portable implementation of such methods. (author's abstract)
HerausgeberDepartment of Statistics and Mathematics, WU Vienna University of Economics and Business
PublikationsstatusVeröffentlicht - 2006


NameResearch Report Series / Department of Statistics and Mathematics

WU Working Paper Reihe

  • Research Report Series / Department of Statistics and Mathematics

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