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  2. Probability mass function - Wikipedia

    en.wikipedia.org/wiki/Probability_mass_function

    The graph of a probability mass function. All the values of this function must be non-negative and sum up to 1. In probability and statistics, a probability mass function (sometimes called probability function or frequency function [1]) is a function that gives the probability that a discrete random variable is exactly equal to some value. [2]

  3. Kernel (statistics) - Wikipedia

    en.wikipedia.org/wiki/Kernel_(statistics)

    In statistics, especially in Bayesian statistics, the kernel of a probability density function (pdf) or probability mass function (pmf) is the form of the pdf or pmf in which any factors that are not functions of any of the variables in the domain are omitted. [1] Note that such factors may well be functions of the parameters of the

  4. Probability-generating function - Wikipedia

    en.wikipedia.org/wiki/Probability-generating...

    If X is a discrete random variable taking values x in the non-negative integers {0,1, ...}, then the probability generating function of X is defined as [1] = ⁡ = = (),where is the probability mass function of .

  5. Yule–Simon distribution - Wikipedia

    en.wikipedia.org/wiki/Yule–Simon_distribution

    In probability and statistics, the Yule–Simon distribution is a discrete probability distribution named after Udny Yule and Herbert A. Simon. Simon originally called it the Yule distribution. [1] The probability mass function (pmf) of the Yule–Simon (ρ) distribution is

  6. Probability distribution - Wikipedia

    en.wikipedia.org/wiki/Probability_distribution

    Probability mass function (pmf): function that gives the probability that a discrete random variable is equal to some value. Frequency distribution: a table that displays the frequency of various outcomes in a sample.

  7. Poisson binomial distribution - Wikipedia

    en.wikipedia.org/wiki/Poisson_binomial_distribution

    For computing the PMF, a DFT algorithm or a recursive algorithm can be specified to compute the exact PMF, and approximation methods using the normal and Poisson distribution can also be specified. poibin - Python implementation - can compute the PMF and CDF, uses the DFT method described in the paper for doing so.

  8. Characteristic function (probability theory) - Wikipedia

    en.wikipedia.org/wiki/Characteristic_function...

    The formula in the definition of characteristic function allows us to compute φ when we know the distribution function F (or density f). If, on the other hand, we know the characteristic function φ and want to find the corresponding distribution function, then one of the following inversion theorems can be used. Theorem.

  9. Category:Table templates - Wikipedia

    en.wikipedia.org/wiki/Category:Table_templates

    Templates used in the creation and formatting of tables and columns. See also {{ List to table }} and its related Category:Articles requiring tables ; and Category:Multi-column templates for simple columns without tables.