# Rejection sampling

## Computational statistics technique / From Wikipedia, the free encyclopedia

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In numerical analysis and computational statistics, **rejection sampling** is a basic technique used to generate observations from a distribution. It is also commonly called the **acceptance-rejection method** or "accept-reject algorithm" and is a type of exact simulation method. The method works for any distribution in $\mathbb {R} ^{m}$ with a density.

Rejection sampling is based on the observation that to sample a random variable in one dimension, one can perform a uniformly random sampling of the two-dimensional Cartesian graph, and keep the samples in the region under the graph of its density function.[1][2][3] Note that this property can be extended to *N*-dimension functions.