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  2. List of random number generators - Wikipedia

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

    Random number generators are important in many kinds of technical applications, including physics, engineering or mathematical computer studies (e.g., Monte Carlo simulations), cryptography and gambling (on game servers ). This list includes many common types, regardless of quality or applicability to a given use case.

  3. Random seed - Wikipedia

    en.wikipedia.org/wiki/Random_seed

    A random seed (or seed state, or just seed) is a number (or vector) used to initialize a pseudorandom number generator. For a seed to be used in a pseudorandom number generator, it does not need to be random.

  4. Random number generation - Wikipedia

    en.wikipedia.org/wiki/Random_number_generation

    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. This means that the particular outcome sequence will contain some patterns detectable in hindsight but impossible to foresee.

  5. Pseudorandom number generator - Wikipedia

    en.wikipedia.org/wiki/Pseudorandom_number_generator

    A pseudorandom number generator (PRNG), also known as a deterministic random bit generator (DRBG), is an algorithm for generating a sequence of numbers whose properties approximate the properties of sequences of random numbers.

  6. Randomness test - Wikipedia

    en.wikipedia.org/wiki/Randomness_test

    Randomness test. A randomness test (or test for randomness ), in data evaluation, is a test used to analyze the distribution of a set of data to see whether it can be described as random (patternless). In stochastic modeling, as in some computer simulations, the hoped-for randomness of potential input data can be verified, by a formal test for ...

  7. Wichmann–Hill - Wikipedia

    en.wikipedia.org/wiki/Wichmann–Hill

    Wichmann–Hill is a pseudorandom number generator proposed in 1982 by Brian Wichmann and David Hill. It consists of three linear congruential generators with different prime moduli, each of which is used to produce a uniformly distributed number between 0 and 1.

  8. Pseudorandom binary sequence - Wikipedia

    en.wikipedia.org/wiki/Pseudorandom_binary_sequence

    A pseudorandom binary sequence (PRBS), pseudorandom binary code or pseudorandom bitstream is a binary sequence that, while generated with a deterministic algorithm, is difficult to predict [1] and exhibits statistical behavior similar to a truly random sequence.

  9. Inverse transform sampling - Wikipedia

    en.wikipedia.org/wiki/Inverse_transform_sampling

    Inverse transform sampling (also known as inversion sampling, the inverse probability integral transform, the inverse transformation method, or the Smirnov transform) is a basic method for pseudo-random number sampling, i.e., for generating sample numbers at random from any probability distribution given its cumulative distribution function .

  10. ACORN (random number generator) - Wikipedia

    en.wikipedia.org/.../ACORN_(random_number_generator)

    The ACORN or ″ A dditive Co ngruential R andom N umber″ generators are a robust family of pseudorandom number generators (PRNGs) for sequences of uniformly distributed pseudo-random numbers, introduced in 1989 and still valid in 2019, thirty years later.

  11. Microsoft Excel - Wikipedia

    en.wikipedia.org/wiki/Microsoft_Excel

    Microsoft Excel is a spreadsheet editor developed by Microsoft for Windows, macOS, Android, iOS and iPadOS. It features calculation or computation capabilities, graphing tools, pivot tables, and a macro programming language called Visual Basic for Applications (VBA). Excel forms part of the Microsoft 365 suite of software.