# Non-uniform random variate generation

## Generating pseudo-random numbers that follow a probability distribution / From Wikipedia, the free encyclopedia

**Non-uniform random variate generation** or **pseudo-random number sampling** is the numerical practice of generating pseudo-random numbers (PRN) that follow a given probability distribution.
Methods are typically based on the availability of a uniformly distributed PRN generator. 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.
The first methods were developed for Monte-Carlo simulations in the Manhattan project,^{[citation needed]} published by John von Neumann in the early 1950s.[1]

Generating pseudo-random numbers that follow a probability distribution