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Class library ranlip for multivariate nonuniform random variate generation
This paper describes generation of nonuniform random variates from Lipschitz-continuous densities using acceptance/rejection, and the class library ranlip which implements this method. It is assumed that the required distribution has Lipschitz-continuous density, which is either given analytically or as a black box. The algorithm builds a piecewise constant upper approximation to the density (the hat function), using a large number of its values and subdivision of the domain into hyperrectangles. The class library ranlip provides very competitive preprocessing and generation times, and yields small rejection constant, which is a measure of efficiency of the generation step. It exhibits good performance for up to five variables, and provides the user with a black box nonuniform random variate generator for a large class of distributions, in particular, multimodal distributions. It will be valuable for researchers who frequently face the task of sampling from unusual distributions, for which specialized random variate generators are not available.
History
Journal
Computer physics communicationsVolume
170Issue
1Pagination
93 - 108Publisher
North-Holland Pub. Co.,Location
Amsterdam, NetherlandsPublisher DOI
ISSN
0010-4655eISSN
1879-2944Language
engPublication classification
C1 Refereed article in a scholarly journalCopyright notice
2005, Elsevier B.V.Usage metrics
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