Content deleted Content added
Replace Category:Sampling techniques with Category:Monte Carlo methods. |
No edit summary |
||
Line 1:
'''Inverse transform sampling''' , also known as the probability integral transform, is a method of sampling a number at random from any [[probability distribution]] given its [[cumulative distribution function]] (cdf). This method is generally applicable, but may be too computationally expensive in practice for some probability distributions. See [[Box-Muller transform]] for an example of an algorithm which is less general but more computationally efficient.
==Definition==
The [[probability integral transform]] states that if ''X'' is continuous random variable with a strictly increasing cumulative distribution function F<sub>x</sub>, and if Y = F<sub>X</sub>(X), then Y has a uniform distribution on [0,1].
==The method==
| |||