One thing you could do is to apply von Neumann de-biasing to convert a string of output bits from your biased PRNG to an unbiased string, and test the de-biased output. If such tests pass I don't know that you can be satisfied thaty your biased PRNG is close to a theorieical biased random bit stream, but if they fail that should indicate a problem.
Robert E. Beaudoin On Wed, 7 Dec 2022 11:05:53 -0500 David Lowry-Duda <da...@lowryduda.com> wrote: > Inspired by the recent thread about pseudorandom number generators on > python-ideas (where I also mistakenly first wrote this message), 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 -- https://mail.python.org/mailman/listinfo/python-list
