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In probability theory, the law of rare events or Poisson limit theorem states that the Poisson distribution may be used as an approximation to the binomial distribution, under certain conditions. [1] The theorem was named after Siméon Denis Poisson (1781–1840). A generalization of this theorem is Le Cam's theorem
In probability theory and statistics, the Poisson distribution (/ ˈ p w ɑː s ɒ n /; French pronunciation:) is a discrete probability distribution that expresses the probability of a given number of events occurring in a fixed interval of time if these events occur with a known constant mean rate and independently of the time since the last event. [1]
A visual depiction of a Poisson point process starting. In probability theory, statistics and related fields, a Poisson point process (also known as: Poisson random measure, Poisson random point field and Poisson point field) is a type of mathematical object that consists of points randomly located on a mathematical space with the essential feature that the points occur independently of one ...
Download as PDF; Printable version ... In probability theory, Le Cam's theorem, named after Lucien Le Cam ... this generalizes the usual Poisson limit theorem.
Cameron–Martin theorem; Campbell's theorem (probability) Central limit theorem; Characterization of probability distributions; Chung–Erdős inequality; Condorcet's jury theorem; Continuous mapping theorem; Contraction principle (large deviations theory) Coupon collector's problem; Cox's theorem; Cramér–Wold theorem; Cramér's theorem ...
The characteristic function approach is particularly useful in analysis of linear combinations of independent random variables: a classical proof of the Central Limit Theorem uses characteristic functions and Lévy's continuity theorem. Another important application is to the theory of the decomposability of random variables.
Central limit theorem. Central limit theorem (illustration) – redirects to Illustration of the central limit theorem; Central limit theorem for directional statistics; Lyapunov's central limit theorem; Martingale central limit theorem; Central moment; Central tendency; Census; Cepstrum; CHAID – CHi-squared Automatic Interaction Detector
A renewal process has asymptotic properties analogous to the strong law of large numbers and central limit theorem. The renewal function () (expected number of arrivals) and reward function () (expected reward value) are of key importance in renewal theory. The renewal function satisfies a recursive integral equation, the renewal equation.