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In general statistics and probability, "divergence" generally refers to any kind of function ... For example, when D is an f-divergence [6] for some function ƒ ...
In mathematical statistics, the Kullback–Leibler (KL) divergence (also called relative entropy and I-divergence [1]), denoted (), is a type of statistical distance: a measure of how much a model probability distribution Q is different from a true probability distribution P.
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.
It is ubiquitous in nature and statistics due to the central limit theorem: every variable that can be modelled as a sum of many small independent, identically distributed variables with finite mean and variance is approximately normal. The normal-exponential-gamma distribution; The normal-inverse Gaussian distribution
The total variation distance is related to the Kullback–Leibler divergence by Pinsker’s inequality: (,) ().One also has the following inequality, due to Bretagnolle and Huber [2] (see also [3]), which has the advantage of providing a non-vacuous bound even when () >:
The different notions of convergence capture different properties about the sequence, with some notions of convergence being stronger than others. For example, convergence in distribution tells us about the limit distribution of a sequence of random variables. This is a weaker notion than convergence in probability, which tells us about the ...
F-divergence; F-statistics – population genetics; F-test; F-test of equality of variances; ... Sample (statistics) Sample-continuous process; Sampling (statistics)
In mathematics, specifically statistics and information geometry, a Bregman divergence or Bregman distance is a measure of difference between two points, defined in terms of a strictly convex function; they form an important class of divergences.