Black-box algorithms for sampling from continuous distributions

Wolfgang Hörmann, Josef Leydold

Publikation: Beitrag in Buch/KonferenzbandBeitrag in Konferenzband


For generating non-uniform random variates, black-box algorithms are powerful tools that allow drawing samples from large classes of distri- butions. 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.
Titel des SammelwerksProceedings of the 2006 Winter Simulation Conference
Herausgeber*innen L. F. Perrone, F. P. Wieland, J. Liu, B.G. Lawson, D.M. Nicol and R.M. Fujimoto
ErscheinungsortMonterey, CA, USA
Seiten129 - 136
PublikationsstatusVeröffentlicht - 1 Aug. 2006