# Non-uniform Random Numbers

Non-uniform Random Numbers

Pseudo-random number sampling or non-uniform pseudo-random variate generation is the numerical practice of generating pseudo-random numbers that are distributed according to a given probability distribution.

Methods of sampling a non-uniform distribution are typically based on the availability of a pseudo-random number generator producing numbers X that are uniformly distributed. Computational algorithms are then used to manipulate a single random variate, X, or often several such variates, into a new random variate Y such that these values have the required distribution.

Historically, basic methods of pseudo-random number sampling were developed for Monte-Carlo simulations in the Manhattan project; they were first published by John von Neumann in the early 1950s.

Read more about Non-uniform Random Numbers:  Finite Discrete Distributions, Continuous Distributions, Software Libraries

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Non-uniform Random Numbers - Software Libraries
... GNU Scientific Library has a section entitled "Random Number Distributions" with routines for sampling under more than twenty different distributions ...

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