Black-Box Algorithms for Sampling from Continuous Distributions

Wolfgang Hörmann, Josef Leydold

Publication: Working/Discussion PaperWU Working Paper

Abstract

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)
Original languageEnglish
Place of PublicationVienna
PublisherDepartment of Statistics and Mathematics, WU Vienna University of Economics and Business
Publication statusPublished - 2006

Publication series

NameResearch Report Series / Department of Statistics and Mathematics
No.39

WU Working Paper Series

  • Research Report Series / Department of Statistics and Mathematics

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