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  2. Continuous uniform distribution - Wikipedia

    en.wikipedia.org/wiki/Continuous_uniform...

    In probability theory and statistics, the continuous uniform distributions or rectangular distributions are a family of symmetric probability distributions. Such a distribution describes an experiment where there is an arbitrary outcome that lies between certain bounds. [ 1 ]

  3. Characteristic function (probability theory) - Wikipedia

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

    For example, some authors [6] define φ X (t) = E[e −2πitX], which is essentially a change of parameter. Other notation may be encountered in the literature: p ^ {\displaystyle \scriptstyle {\hat {p}}} as the characteristic function for a probability measure p , or f ^ {\displaystyle \scriptstyle {\hat {f}}} as the characteristic function ...

  4. Probability integral transform - Wikipedia

    en.wikipedia.org/wiki/Probability_integral_transform

    One use for the probability integral transform in statistical data analysis is to provide the basis for testing whether a set of observations can reasonably be modelled as arising from a specified distribution. Specifically, the probability integral transform is applied to construct an equivalent set of values, and a test is then made of ...

  5. Discrete uniform distribution - Wikipedia

    en.wikipedia.org/wiki/Discrete_uniform_distribution

    The problem of estimating the maximum of a discrete uniform distribution on the integer interval [,] from a sample of k observations is commonly known as the German tank problem, following the practical application of this maximum estimation problem, during World War II, by Allied forces seeking to estimate German tank production.

  6. U-statistic - Wikipedia

    en.wikipedia.org/wiki/U-statistic

    In statistical theory, a U-statistic is a class of statistics defined as the average over the application of a given function applied to all tuples of a fixed size. The letter "U" stands for unbiased. [citation needed] In elementary statistics, U-statistics arise naturally in producing minimum-variance unbiased estimators.

  7. Glivenko–Cantelli theorem - Wikipedia

    en.wikipedia.org/wiki/Glivenko–Cantelli_theorem

    The following theorem is central to statistical learning of binary classification tasks. Theorem (Vapnik and Chervonenkis, 1968) [8] Under certain consistency conditions, a universally measurable class of sets is a uniform Glivenko-Cantelli class if and only if it is a Vapnik–Chervonenkis class.

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  9. Univariate distribution - Wikipedia

    en.wikipedia.org/wiki/Univariate_distribution

    Continuous uniform distribution. One of the simplest examples of a discrete univariate distribution is the discrete uniform distribution, where all elements of a finite set are equally likely. It is the probability model for the outcomes of tossing a fair coin, rolling a fair die, etc.