Black-Box Algorithms for Sampling from Continuous Distributions

Hörmann, Wolfgang and Leydold, Josef (2006) Black-Box Algorithms for Sampling from Continuous Distributions. Research Report Series / Department of Statistics and Mathematics, 39. Department of Statistics and Mathematics, WU Vienna University of Economics and Business, Vienna.


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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)

Item Type: Paper
Additional Information: Winter Simulation Conference 2006
Keywords: nonuniform random variate generation / automatic method / black-box method / software
Classification Codes: MSC_65C05, MSC_65C10
Divisions: Departments > Finance, Accounting and Statistics > Statistics and Mathematics
Depositing User: Repository Administrator
Date Deposited: 15 Sep 2006 12:53
Last Modified: 22 Oct 2019 00:41


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