Inverse transform sampling: Difference between revisions

Revision as of 07:16, 30 December 2020

Revision as of 07:36, 30 December 2020

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{{merge|Probability integral transform|date=December 2020}}

'''Inverse transform sampling''' (also known as '''inversion sampling''', the '''inverse probability integral transform''', the '''inverse transformation method''', '''[[Nikolai Smirnov (mathematician)|Smirnov]] transform''', or the '''golden rule'''<ref name=aalto>Aalto University, N. Hyvönen, Computational methods in inverse problems. Twelfth lecture https://noppa.tkk.fi/noppa/kurssi/mat-1.3626/luennot/Mat-1_3626_lecture12.pdf{{dead link|date=November 2017 |bot=InternetArchiveBot |fix-attempted=yes }}</ref>) is a basic method for [[pseudo-random number sampling]], i.e., for generating sample numbers at [[random]] from any [[probability distribution]] given its [[cumulative distribution function]].