Random numbers: Difference between revisions
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Other implementations of Standard ML have their own random number generators. For example, Moscow ML has a <code>Random</code> structure that is different from the one from SML/NJ.
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The SML Basis Library does not provide a routine for uniform deviate generation, and PolyML does not have one. Using a routine from "Monte Carlo" by Fishman (Springer), in the function uniformdeviate, and avoiding the slow IntInf's:
<syntaxhighlight lang="
val urandomlist = fn seed => fn n =>
let
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