I suspect you wouldn't have to test it all, as it would simply be a trivial
redistribution of a standard (already known-good) generator:
def random_bit_666():
return int(random() > 2/3)
For other more sophisticated distributions, again simply verify that your
distribution algorithm is correct and let some library function take care
of the randomness.
On Wed, Dec 7, 2022 at 8:23 AM David Lowry-Duda <da...@lowryduda.com> wrote:
> Inspired by the recent thread on PRNG, I began to wonder: suppose that I
> had a pseudorandom number generator that attempted to generate a
> nonuniform distribution. Suppose for instance that it was to generate a
> 0 bit 2/3 of the time, and a 1 bit 1/3 of the time.
>
> How would one go about testing this PRNG against an idealized (similarly
> biased) PRNG?
>
> - DLD
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