# Do quasi random number generators sample only uniform distribution?

From Wikipedia

quasi-Monte Carlo method is a method for numerical integration and solving some other problems using low-discrepancy sequences (also called quasi-random sequences or sub-random sequences).

It seems to me low discrepancy sequences if seen as random samples are samples of uniform distributions, and not non-uniform distributions. Am I correct or not? Thanks!

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As defined it is usually meant for uniform distribution on $[0,1]$, but you can use the same inversion methods that you use with pseudo-random numbers to get to other distributions. (But you must stay with inversion, most other methods for generating non-uniform distributions will be invalid). –  kjetil b halvorsen Sep 27 '12 at 12:59
@kjetilbhalvorsen: Thanks! Is the acceptance-rejection method still valid for quasi random numbers? What other methods are still valid, and are invalid? –  Tim Sep 29 '12 at 23:29
All methods I have seen that use more tha one random number in input per output non-uniform-random, will be invalid with quasi-random numbers, the point withn quasi-random numbera are just to avoid independence to get better reselts for numerical integration. Inversion uses just one number, so do not depend on independence. –  kjetil b halvorsen Sep 30 '12 at 3:22
Thanks, @kjetilbhalvorsen. The acception-rejection method uses more than one random variables, so is it invalid for quasi? –  Tim Sep 30 '12 at 13:14
Yes. The acceptance-rejection method will be invalid for quasi-random numbers. –  kjetil b halvorsen Sep 30 '12 at 18:31