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Universal Methods

In: Non-Uniform Random Variate Generation

Author

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  • Luc Devroye

    (McGill University, School of Computer Science)

Abstract

In the next two chapters we will apply the tools of the previous chapters in the design of algorithms that are applicable to large families of distributions. Described in terms of a common property, such as the family of all unimodal densities with mode at 0, these families are generally speaking nonparametric in nature. A method that is applicable to such a large family is called a universal method. For example, the rejection method can be used for all bounded densities on [0,1], and is thus a universal method. But to actually apply the rejection method correctly and efficiently would require knowledge of the supremum of the density. This value cannot be estimated in a finite amount of time unless we have more information about the density in question, usually in the form of an explicit analytic definition. Universal methods which do not require anything beyond what is given in the definition of the family are called black box methods.

Suggested Citation

  • Luc Devroye, 1986. "Universal Methods," Springer Books, in: Non-Uniform Random Variate Generation, chapter 0, pages 286-357, Springer.
    • Handle: RePEc:spr:sprchp:978-1-4613-8643-8_7
    DOI: 10.1007/978-1-4613-8643-8_7
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