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  2. Statistical distance - Wikipedia

    en.wikipedia.org/wiki/Statistical_distance

    A metric on a set X is a function (called the distance function or simply distance) d : X × X → R + (where R + is the set of non-negative real numbers). For all x, y, z in X, this function is required to satisfy the following conditions: d(x, y) ≥ 0 (non-negativity) d(x, y) = 0 if and only if x = y (identity of indiscernibles.

  3. Total variation distance of probability measures - Wikipedia

    en.wikipedia.org/wiki/Total_variation_distance...

    The total variation distance (or half the norm) arises as the optimal transportation cost, when the cost function is (,) =, that is, ‖ ‖ = (,) = {(): =, =} = ⁡ [], where the expectation is taken with respect to the probability measure on the space where (,) lives, and the infimum is taken over all such with marginals and , respectively.

  4. Bhattacharyya distance - Wikipedia

    en.wikipedia.org/wiki/Bhattacharyya_distance

    In statistics, the Bhattacharyya distance is a quantity which represents a notion of similarity between two probability distributions. [1] It is closely related to the Bhattacharyya coefficient , which is a measure of the amount of overlap between two statistical samples or populations.

  5. Gower's distance - Wikipedia

    en.wikipedia.org/wiki/Gower's_distance

    In statistics, Gower's distance between two mixed-type objects is a similarity measure that can handle different types of data within the same dataset and is particularly useful in cluster analysis or other multivariate statistical techniques. Data can be binary, ordinal, or continuous variables.

  6. Divergence (statistics) - Wikipedia

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

    In information geometry, a divergence is a kind of statistical distance: a binary function which establishes the separation from one probability distribution to another on a statistical manifold. The simplest divergence is squared Euclidean distance (SED), and divergences can be viewed as

  7. Hellinger distance - Wikipedia

    en.wikipedia.org/wiki/Hellinger_distance

    In probability and statistics, the Hellinger distance (closely related to, although different from, the Bhattacharyya distance) is used to quantify the similarity between two probability distributions. It is a type of f-divergence. The Hellinger distance is defined in terms of the Hellinger integral, which was introduced by Ernst Hellinger in 1909.

  8. Cook's distance - Wikipedia

    en.wikipedia.org/wiki/Cook's_distance

    In statistics, Cook's distance or Cook's D is a commonly used estimate of the influence of a data point when performing a least-squares regression analysis. [1] In a practical ordinary least squares analysis, Cook's distance can be used in several ways: to indicate influential data points that are particularly worth checking for validity; or to indicate regions of the design space where it ...

  9. Official Table of Drops - Wikipedia

    en.wikipedia.org/wiki/Official_Table_of_Drops

    The Official Table of Drops, formerly issued by the British Home Office, is a manual which is used to calculate the appropriate length of rope for long drop hangings. Following a series of failed hangings, including those of John Babbacombe Lee , a committee chaired by Henry Bruce, 1st Baron Aberdare was formed in 1886 to discover and report on ...