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Asked: 2026-05-31T13:08:41+00:00

I am playing around with PRNGs (like Mersenne Twister and rand() function of stdlib)

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I am playing around with PRNGs (like Mersenne Twister and rand() function of stdlib) and I would want a good test that would help me ascertain the quality of random data produced by the PRNGs.
I have calculated the value of Pi using random numbers generated by the PRNGs, and I find rand() and Mersenne Twister to be very close to offer a distinction (do I need to scrutinize after 10 decimal points?).

I do not have much idea about Monte Carlo simulations; please let me know about some algorithm/application (possibly something simple yet which could provide good inferences) that would help me distinguish them in terms of quality.

EDIT 1: I didn’t notice before, but there is a similar thread: How to test random numbers?

EDIT 2: I am not able to interprete the results of NIST, as mentioned in one of the comments. I got this idea of visually interpreting the pattern (if any) from random.org and am following that because of it’s simplicity. I would be very glad if someone could comment on the process of my testing:

  1. Generate N randoms from [0,1] using rand() and MT1997
  2. if (round(genrand_real1() / rand_0_1())) then red pixel, else black

As I understand that this is not a very precise solution, but if this provides a reasonable estimate, then I could live with this at the present moment.

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1 Answer

  1. Editorial Team

    There are two standard test suites for testing random numbers.

    1. NIST test suite. They have an implementation in C.
    2. Diehard Test Suite (developed by George Marsaglia). There is a C library implementation of these tests.

    There is a R interface to the Dieharder library, called RDieHarder. This library provides an interface to both the NIST and Diehard test suites.

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