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  2. Exponential distribution - Wikipedia

    en.wikipedia.org/wiki/Exponential_distribution

    In probability theory and statistics, the exponential distribution or negative exponential distribution is the probability distribution of the distance between events in a Poisson point process, i.e., a process in which events occur continuously and independently at a constant average rate; the distance parameter could be any meaningful mono-dimensional measure of the process, such as time ...

  3. Error function - Wikipedia

    en.wikipedia.org/wiki/Error_function

    Given a random variable X ~ Norm[μ,σ] (a normal distribution with mean μ and standard deviation σ) and a constant L > μ, it can be shown via integration by substitution: [] = + ⁡ ⁡ (()) where A and B are certain numeric constants.

  4. Exp4j - Wikipedia

    en.wikipedia.org/wiki/Exp4j

    exp4j is a small Java library for evaluation of mathematical expressions. [1] It implements Dijkstra's Shunting-yard algorithm to translate expressions from infix notation to Reverse Polish notation and calculates the result using a simple Stack algorithm.

  5. Erlang distribution - Wikipedia

    en.wikipedia.org/wiki/Erlang_distribution

    The Erlang distribution is the distribution of a sum of independent exponential variables with mean / each. Equivalently, it is the distribution of the time until the kth event of a Poisson process with a rate of . The Erlang and Poisson distributions are complementary, in that while the Poisson distribution counts the events that occur in a ...

  6. Log probability - Wikipedia

    en.wikipedia.org/wiki/Log_probability

    Since most common probability distributions—notably the exponential family—are only logarithmically concave, [2] [3] and concavity of the objective function plays a key role in the maximization of a function such as probability, optimizers work better with log probabilities.

  7. Gamma distribution - Wikipedia

    en.wikipedia.org/wiki/Gamma_distribution

    In probability theory and statistics, the gamma distribution is a versatile two-parameter family of continuous probability distributions. [1] The exponential distribution, Erlang distribution, and chi-squared distribution are special cases of the gamma distribution. [2] There are two equivalent parameterizations in common use:

  8. Modular exponentiation - Wikipedia

    en.wikipedia.org/wiki/Modular_exponentiation

    Go's big.Int type contains an Exp() (exponentiation) method whose third parameter, if non-nil, is the modulus PHP 's BC Math library has a bcpowmod() function [4] to perform modular exponentiation The GNU Multiple Precision Arithmetic Library (GMP) library contains a mpz_powm() function [5] to perform modular exponentiation

  9. Lévy distribution - Wikipedia

    en.wikipedia.org/wiki/Lévy_distribution

    In probability theory and statistics, the Lévy distribution, named after Paul Lévy, is a continuous probability distribution for a non-negative random variable. In spectroscopy, this distribution, with frequency as the dependent variable, is known as a van der Waals profile. [note 1] It is a special case of the inverse-gamma distribution.