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  2. Statistical distance - Wikipedia

    en.wikipedia.org/wiki/Statistical_distance

    In statistics, probability theory, and information theory, a statistical distance quantifies the distance between two statistical objects, which can be two random variables, or two probability distributions or samples, or the distance can be between an individual sample point and a population or a wider sample of points.

  3. 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.

  4. 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.

  5. Cohen's h - Wikipedia

    en.wikipedia.org/wiki/Cohen's_h

    In statistics, Cohen's h, popularized by Jacob Cohen, is a measure of distance between two proportions or probabilities. Cohen's h has several related uses: It can be used to describe the difference between two proportions as "small", "medium", or "large". It can be used to determine if the difference between two proportions is "meaningful".

  6. Divergence (statistics) - Wikipedia

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

    The two most important divergences are the relative entropy (Kullback–Leibler divergence, KL divergence), which is central to information theory and statistics, and the squared Euclidean distance (SED). Minimizing these two divergences is the main way that linear inverse problems are solved, via the principle of maximum entropy and least ...

  7. Similarity measure - Wikipedia

    en.wikipedia.org/wiki/Similarity_measure

    The Euclidean distance formula is used to find the distance between two points on a plane, which is visualized in the image below. Manhattan distance is commonly used in GPS applications, as it can be used to find the shortest route between two addresses. [citation needed] When you generalize the Euclidean distance formula and Manhattan ...

  8. Total variation distance of probability measures - Wikipedia

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

    Total variation distance is half the absolute area between the two curves: Half the shaded area above. In probability theory, the total variation distance is a statistical distance between probability distributions, and is sometimes called the statistical distance, statistical difference or variational distance.

  9. Stein's method - Wikipedia

    en.wikipedia.org/wiki/Stein's_method

    Stein's method is a general method in probability theory to obtain bounds on the distance between two probability distributions with respect to a probability metric.It was introduced by Charles Stein, who first published it in 1972, [1] to obtain a bound between the distribution of a sum of -dependent sequence of random variables and a standard normal distribution in the Kolmogorov (uniform ...