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  2. List of random number generators - Wikipedia

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

    These approaches combine a pseudo-random number generator (often in the form of a block or stream cipher) with an external source of randomness (e.g., mouse movements, delay between keyboard presses etc.). /dev/random – Unix-like systems; CryptGenRandom – Microsoft Windows; Fortuna

  3. Marsaglia polar method - Wikipedia

    en.wikipedia.org/wiki/Marsaglia_polar_method

    The Marsaglia polar method [1] is a pseudo-random number sampling method for generating a pair of independent standard normal random variables. [2]Standard normal random variables are frequently used in computer science, computational statistics, and in particular, in applications of the Monte Carlo method.

  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. Ziggurat algorithm - Wikipedia

    en.wikipedia.org/wiki/Ziggurat_algorithm

    To use the same algorithm to check if the point is in the central region, generate a fictitious x 0 = A/y 1. This will generate points with x < x 1 with the correct frequency, and in the rare case that layer 0 is selected and x ≥ x 1, use a special fallback algorithm to select a point at random from the tail. Because the fallback algorithm is ...

  6. 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 ]

  7. Stochastic simulation - Wikipedia

    en.wikipedia.org/wiki/Stochastic_simulation

    The problem is that the computer is highly deterministic machine—basically, behind each process there is always an algorithm, a deterministic computation changing inputs to outputs; therefore it is not easy to generate uniformly spread random numbers over a defined interval or set. [1] A random number generator is a device capable of ...

  8. Multiply-with-carry pseudorandom number generator - Wikipedia

    en.wikipedia.org/wiki/Multiply-with-carry...

    A linear congruential generator with base b = 2 32 is implemented as + = (+) , where c is a constant. If a ≡ 1 (mod 4) and c is odd, the resulting base-2 32 congruential sequence will have period 2 32.

  9. Applications of randomness - Wikipedia

    en.wikipedia.org/wiki/Applications_of_randomness

    Random numbers have uses in physics such as electronic noise studies, engineering, and operations research. Many methods of statistical analysis, such as the bootstrap method, require random numbers. Monte Carlo methods in physics and computer science require random numbers. Random numbers are often used in parapsychology as a test of precognition.