Abstract
There are situations in the practice of statistical research where continuous distributions are not characterized by their density or cumulative distribution function. Instead some other functions like the hazard rate (Sect. 9.1), the characteristic function (Sect. 9.4), or a sequence of Fourier coefficients (Sect. 9.3) are known. In such cases it can be very useful to have the possibility to sample directly from these distributions without computing the density, which is often very difficult and cumbersome in such situations. Luc Devroye (1981; 1984a; 1986c; 1986d; 1989) has introduced most of these methods. We give an overview and present the details of those algorithms that seem to be most useful in practice; among them a new automatic algorithm for distributions with increasing hazard rate.
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© 2004 Springer-Verlag Berlin Heidelberg
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Hörmann, W., Leydold, J., Derflinger, G. (2004). Distributions Where the Density Is Not Known Explicitly. In: Automatic Nonuniform Random Variate Generation. Statistics and Computing. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-05946-3_9
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DOI: https://doi.org/10.1007/978-3-662-05946-3_9
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-07372-4
Online ISBN: 978-3-662-05946-3
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