• Thumbnail for Markov chain
    In probability theory and statistics, a Markov chain or Markov process is a stochastic process describing a sequence of possible events in which the probability...
    94 KB (12,750 words) - 22:22, 19 December 2024
  • In statistics, Markov chain Monte Carlo (MCMC) is a class of algorithms used to draw samples from a probability distribution. Given a probability distribution...
    29 KB (3,126 words) - 05:23, 19 December 2024
  • A hidden Markov model (HMM) is a Markov model in which the observations are dependent on a latent (or hidden) Markov process (referred to as X {\displaystyle...
    52 KB (6,811 words) - 04:08, 22 December 2024
  • examples of Markov chains and Markov processes in action. All examples are in the countable state space. For an overview of Markov chains in general state...
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  • In the mathematical theory of probability, an absorbing Markov chain is a Markov chain in which every state can reach an absorbing state. An absorbing...
    12 KB (1,762 words) - 20:08, 14 December 2024
  • A continuous-time Markov chain (CTMC) is a continuous stochastic process in which, for each state, the process will change state according to an exponential...
    23 KB (4,241 words) - 22:53, 10 December 2024
  • Markov chain geostatistics uses Markov chain spatial models, simulation algorithms and associated spatial correlation measures (e.g., transiogram) based...
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  • In mathematics, the quantum Markov chain is a reformulation of the ideas of a classical Markov chain, replacing the classical definitions of probability...
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  • Thumbnail for Discrete-time Markov chain
    In probability, a discrete-time Markov chain (DTMC) is a sequence of random variables, known as a stochastic process, in which the value of the next variable...
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  • The Lempel–Ziv–Markov chain algorithm (LZMA) is an algorithm used to perform lossless data compression. It has been used in the 7z format of the 7-Zip...
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  • distribution of a previous state. An example use of a Markov chain is Markov chain Monte Carlo, which uses the Markov property to prove that a particular method...
    10 KB (1,175 words) - 07:55, 18 July 2024
  • from its connection to Markov chains, a concept developed by the Russian mathematician Andrey Markov. The "Markov" in "Markov decision process" refers...
    34 KB (5,086 words) - 15:40, 20 December 2024
  • Thumbnail for Andrey Markov
    known as the Markov chain. He was also a strong, close to master-level, chess player. Markov and his younger brother Vladimir Andreyevich Markov (1871–1897)...
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  • Thumbnail for Markov property
    stochastic process satisfying the Markov property is known as a Markov chain. A stochastic process has the Markov property if the conditional probability...
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  • stochastic matrix is a square matrix used to describe the transitions of a Markov chain. Each of its entries is a nonnegative real number representing a probability...
    19 KB (2,798 words) - 20:31, 26 November 2024
  • Markov chain is the time until the Markov chain is "close" to its steady state distribution. More precisely, a fundamental result about Markov chains...
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  • In the mathematical theory of random processes, the Markov chain central limit theorem has a conclusion somewhat similar in form to that of the classic...
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  • counting measures. The Markov chain is ergodic, so the shift example from above is a special case of the criterion. Markov chains with recurring communicating...
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  • Thumbnail for Random walk
    ) {\displaystyle O(a+b)} in the general one-dimensional random walk Markov chain. Some of the results mentioned above can be derived from properties of...
    55 KB (7,649 words) - 13:39, 25 November 2024
  • characterize continuous-time Markov processes. In particular, they describe how the probability of a continuous-time Markov process in a certain state changes...
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  • balance in kinetics seem to be clear. A Markov process is called a reversible Markov process or reversible Markov chain if there exists a positive stationary...
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  • Thumbnail for Finite-state machine
    Library of Congress Card Catalog Number 65-17394. "We may think of a Markov chain as a process that moves successively through a set of states s1, s2,...
    40 KB (4,523 words) - 23:47, 9 December 2024
  • Chapman–Kolmogorov equation (category Markov processes)
    equation Examples of Markov chains Category of Markov kernels Perrone (2024), pp. 10–11 Pavliotis, Grigorios A. (2014). "Markov Processes and the Chapman–Kolmogorov...
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  • Gauss–Markov theorem Gauss–Markov process Markov blanket Markov boundary Markov chain Markov chain central limit theorem Additive Markov chain Markov additive...
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  • Thumbnail for Computational statistics
    computationally intensive statistical methods including resampling methods, Markov chain Monte Carlo methods, local regression, kernel density estimation, artificial...
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  • Andrey A. Markov Markov chain, a mathematical process useful for statistical modeling Markov random field, a set of random variables having a Markov property...
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  • Thumbnail for Stochastic process
    scientists. Markov processes and Markov chains are named after Andrey Markov who studied Markov chains in the early 20th century. Markov was interested...
    168 KB (18,653 words) - 09:51, 14 December 2024
  • mathematical theory of Markov chains, the Markov chain tree theorem is an expression for the stationary distribution of a Markov chain with finitely many...
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  • Thumbnail for Metropolis–Hastings algorithm
    statistics and statistical physics, the Metropolis–Hastings algorithm is a Markov chain Monte Carlo (MCMC) method for obtaining a sequence of random samples...
    30 KB (4,556 words) - 16:16, 6 December 2024
  • However, with the advent of powerful computers and new algorithms like Markov chain Monte Carlo, Bayesian methods have seen increasing use within statistics...
    19 KB (2,395 words) - 16:41, 22 December 2024