Titlebook: Non-Uniform Random Variate Generation; Luc Devroye Book 1986 Springer Science+Business Media New York 1986 Area.Generator.Random variable.

Frequency-Range

Exposure

Fsh238

Discrete Random Variates,riable is a random variable which takes with probability one values in a given countable set of points. Since there is a one-to-one correspondence between any countable set and the nonnegative integers, it is clear that we need not consider the general case. In most cases of interest to the practiti

地牢

Buttress

Offensive

The Poisson Process,e simulated. The methods of simulation vary with the type of Poisson point process, i.e. with the space in which the process occurs, and with the homogeneity or nonhomogeneity of the process. We will not be concerned with the genesis of the Poisson point process, or with important applications in va

领袖气质

Universal Methods,utions. 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 .. For example, the rejection method can be used for all bounded

宿醉

Table Methods for Continuous Random Variates,te is generated by the inversion method, it pays to compute and store the individual probabilities .. beforehand. This information can speed up sequential search, or could be used in the method of guide tables. For continuous random varlates, the same remains true. Because we know many ultra fast di

JAUNT

Nostalgia

Discrete Univariate Distributions,istributions. These distributions are the fundamental building blocks in discrete probability. It is impossible to cover most distributions commonly used in practice. Indeed, there is a strong tendency to work more and more with so-called generalized distributions. These distributions are either def