A Markov chain or Markov process is a stochastic process describing a sequence of possible events in which the probability of each event depends only on...
93 KB (12,527 words) - 17:37, 16 October 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 (3,091 words) - 22:08, 27 September 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...
51 KB (6,799 words) - 21:37, 23 September 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...
14 KB (2,429 words) - 21:01, 8 July 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) - 01:52, 27 June 2024
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 (1,760 words) - 17:23, 25 May 2024
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...
25 KB (4,252 words) - 01:57, 27 June 2024
Markov chain geostatistics uses Markov chain spatial models, simulation algorithms and associated spatial correlation measures (e.g., transiogram) based...
2 KB (234 words) - 15:05, 12 September 2021
The Lempel–Ziv–Markov chain algorithm (LZMA) is an algorithm used to perform lossless data compression. It has been under development since either 1996...
31 KB (3,619 words) - 04:31, 24 August 2024
In mathematics, the quantum Markov chain is a reformulation of the ideas of a classical Markov chain, replacing the classical definitions of probability...
2 KB (201 words) - 21:28, 18 January 2022