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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. Yule–Simon distribution - Wikipedia

    en.wikipedia.org/wiki/Yule–Simon_distribution

    This means that the tail of the Yule–Simon distribution is a realization of Zipf's law: (;) can be used to model, for example, the relative frequency of the th most frequent word in a large collection of text, which according to Zipf's law is inversely proportional to a (typically small) power of .

  5. Solid Converter PDF - Wikipedia

    en.wikipedia.org/wiki/Solid_Converter_PDF

    Solid Converter PDF is document reconstruction software from Solid Documents which converts PDF files to editable formats. Originally released for the Microsoft Windows operating system, a Mac OS X version was released in 2010. The current versions are Solid Converter PDF 9.0 for Windows and Solid PDF to Word for Mac 2.1.

  6. Skellam distribution - Wikipedia

    en.wikipedia.org/wiki/Skellam_distribution

    The probability mass function of a Poisson-distributed random variable with mean μ is given by (;) =!.for (and zero otherwise). The Skellam probability mass function for the difference of two independent counts = is the convolution of two Poisson distributions: (Skellam, 1946)

  7. Convolution of probability distributions - Wikipedia

    en.wikipedia.org/wiki/Convolution_of_probability...

    The probability distribution of the sum of two or more independent random variables is the convolution of their individual distributions. The term is motivated by the fact that the probability mass function or probability density function of a sum of independent random variables is the convolution of their corresponding probability mass functions or probability density functions respectively.

  8. Zamzar - Wikipedia

    en.wikipedia.org/wiki/Zamzar

    [7] Users can type in a URL or upload one or more files (if they are all of the same format) from their computer; Zamzar will then convert the file(s) to another user-specified format, such as an Adobe PDF file to a Microsoft Word document. [8] Once conversion is complete, users can immediately download the file from their web browser. [9]

  9. Probability-generating function - Wikipedia

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

    In probability theory, the probability generating function of a discrete random variable is a power series representation (the generating function) of the probability mass function of the random variable.

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