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  2. List of random number generators - Wikipedia

    en.wikipedia.org/wiki/List_of_random_number...

    Default generator in R and the Python language starting from version 2.3. Xorshift: 2003 G. Marsaglia [26] It is a very fast sub-type of LFSR generators. Marsaglia also suggested as an improvement the xorwow generator, in which the output of a xorshift generator is added with a Weyl sequence.

  3. Module:Random - Wikipedia

    en.wikipedia.org/wiki/Module:Random

    The date function outputs a random date. {{#invoke:random|date|timestamp1|timestamp2|format=date format|same=yes}} If no timestamp arguments are specified, the module outputs a random date in the current year. If timestamp1 and timestamp2 are specified, the module outputs a random date between the two timestamps.

  4. Random number generation - Wikipedia

    en.wikipedia.org/wiki/Random_number_generation

    Dice are an example of a mechanical hardware random number generator. When a cubical die is rolled, a random number from 1 to 6 is obtained. Random number generation is a process by which, often by means of a random number generator (RNG), a sequence of numbers or symbols that cannot be reasonably predicted better than by random chance is generated.

  5. Pseudorandom number generator - Wikipedia

    en.wikipedia.org/wiki/Pseudorandom_number_generator

    It can be shown that if is a pseudo-random number generator for the uniform distribution on (,) and if is the CDF of some given probability distribution , then is a pseudo-random number generator for , where : (,) is the percentile of , i.e. ():= {: ()}. Intuitively, an arbitrary distribution can be simulated from a simulation of the standard ...

  6. Generator (computer programming) - Wikipedia

    en.wikipedia.org/wiki/Generator_(computer...

    For example, a ranged loop like for x = 1 to 10 can be implemented as iteration through a generator, as in Python's for x in range(1, 10). Further, break can be implemented as sending finish to the generator and then using continue in the loop.

  7. Applications of randomness - Wikipedia

    en.wikipedia.org/wiki/Applications_of_randomness

    For these applications, truly random numbers are ideal, and very high quality pseudo-random numbers are necessary if truly random numbers, such as coming from a hardware random number generator, are unavailable. Truly random numbers are absolutely required to be assured of the theoretical security provided by the one-time pad — the only ...

  8. Linear congruential generator - Wikipedia

    en.wikipedia.org/wiki/Linear_congruential_generator

    For a specific example, an ideal random number generator with 32 bits of output is expected (by the Birthday theorem) to begin duplicating earlier outputs after √ m ≈ 2 16 results. Any PRNG whose output is its full, untruncated state will not produce duplicates until its full period elapses, an easily detectable statistical flaw. [36]

  9. Mersenne Twister - Wikipedia

    en.wikipedia.org/wiki/Mersenne_Twister

    The 'Extract number' section shows an example where integer 0 has already been output and the index is at integer 1. 'Generate numbers' is run when all integers have been output. For a w -bit word length, the Mersenne Twister generates integers in the range [ 0 , 2 w − 1 ] {\displaystyle [0,2^{w}-1]} .