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==Link==
The link in the reference at the bottom is 404'ed. (Non-Uniform Random Variate Generation)
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I heard that the the inverse method also works for the discontinuous case, despite the discontinuity. [[User:Jackzhp|Jackzhp]] ([[User talk:Jackzhp|talk]]) 22:38, 28 January 2011 (UTC)
:In fact, it works for the general case using the generalized inverse. Details can be found [https://math.stackexchange.com/questions/4610019/inverse-transform-sampling-for-general-random-variables here]. [[User:Sowhates|Sowhates]] ([[User talk:Sowhates|talk]]) 09:24, 3 January 2023 (UTC)
== Unclear value in table ==
Someone should edit 1-2^{-52} to something that makes sense. is it supposed to be 1 - 1/(2^{52}) ?? <!-- Template:Unsigned --><span class="autosigned" style="font-size:85%;">— Preceding [[Wikipedia:Signatures|unsigned]] comment added by [[User:Aditya8795|Aditya8795]] ([[User talk:Aditya8795#top|talk]] • [[Special:Contributions/Aditya8795|contribs]]) 17:29, 9 August 2018 (UTC)</span>
:Yes; that's it; I've re-formatted with a superscript to make this clearer. [[User:Klbrain|Klbrain]] ([[User talk:Klbrain|talk]]) 10:15, 24 June 2021 (UTC)
{{resolved}}
== Long-winded intro ==
The concept is pretty simple: to generate a random sample X with CDF, you can take Y from a uniform distribution and transform it via X = invCDF(Y).
I think the intro should be much more concise, and clearly get to the point. I shouldn't need to dig through the article for 2 minutes to figure out how inverse transform sampling works. <!-- Template:Unsigned --><span class="autosigned" style="font-size:85%;">— Preceding [[Wikipedia:Signatures|unsigned]] comment added by [[User:Azmisov|Azmisov]] ([[User talk:Azmisov#top|talk]] • [[Special:Contributions/Azmisov|contribs]]) 20:04, 21 December 2021 (UTC)</span> <!--Autosigned by SineBot-->
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