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• W2138460900 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." @default.
• W2138460900 created "2016-06-24" @default.
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• W2138460900 date "2006-12-03" @default.
• W2138460900 modified "2023-10-08" @default.
• W2138460900 title "Black-box algorithms for sampling from continuous distributions" @default.
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• W2138460900 doi "https://doi.org/10.5555/1218112.1218140" @default.
• W2138460900 hasPublicationYear "2006" @default.
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