A Markov chain or Markov process is a stochastic model describing a sequence of possible events in which the probability of each event depends only on... 102 KB (13,251 words) - 02:09, 4 May 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... 28 KB (3,060 words) - 05:57, 19 April 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 (6,740 words) - 07:49, 7 April 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) - 12:39, 25 April 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) - 07:24, 24 February 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... 15 KB (2,485 words) - 07:44, 24 February 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 |
The Lempel–Ziv–Markov chain algorithm (LZMA) is an algorithm used to perform lossless data compression. It has been under development since either 1996... 48 KB (6,152 words) - 12:10, 4 April 2024 |
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 (1,201 words) - 14:09, 8 February 2024 |