after the Russian mathematician Andrey Markov. The term strong Markov property is similar to the Markov property, except that the meaning of "present"...

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...

not on the events that occurred before it (that is, it assumes the Markov property). Generally, this assumption enables reasoning and computation with...

probability, a Markov random field (MRF), Markov network or undirected graphical model is a set of random variables having a Markov property described by...

the underlying structure of state transitions that still follow the Markov property. The process is called a "decision process" because it involves making...

Michael O. Rabin (1958). A Markov property P of finitely presentable groups is one for which: P is an abstract property, that is, P is preserved under...

is a Bayesian network with respect to G if it satisfies the local Markov property: each variable is conditionally independent of its non-descendants...

last equation is in the form of a local Markov property. Measures with this property are sometimes called Markov random fields. More strongly, the converse...

ergodic theory, a Markov operator is an operator on a certain function space that conserves the mass (the so-called Markov property). If the underlying...

decision process Markov's inequality Markov brothers' inequality Markov information source Markov network Markov number Markov property Markov process Stochastic...

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...

Andrey Markov: A Markov chain or Markov process, a stochastic model describing a sequence of possible events The Markov property, the memoryless property of...

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...

Markov Markov chain, a mathematical process useful for statistical modeling Markov random field, a set of random variables having a Markov property described...

have a number of nice properties, which include sample and Feller continuity; the Markov property; the strong Markov property; the existence of an infinitesimal...

Gauss–Markov theorem Gauss–Markov process Markov blanket Markov boundary Markov chain Markov chain central limit theorem Additive Markov chain Markov additive...

In statistics, Markov chain Monte Carlo (MCMC) is a class of algorithms used to draw samples from a probability distribution. Given a probability distribution...

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...

contains 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...

but here we have only the weaker assumption that the process has the Markov property; and g {\textstyle g} is some (measurable) real-valued function for...

intelligence, which employ Markov networks, and Markov logic networks. The Gibbs measure is also the unique measure that has the property of maximizing the entropy...

job arrivals to a queue over time. If a process has the Markov property, it is said to be a Markov counting process. Intensity of counting processes Ross...

Markov chain models, where each random variable in a sequence with a Markov property depends on a fixed number of random variables, in VOM models this number...

their mathematical properties, stochastic processes can be grouped into various categories, which include random walks, martingales, Markov processes, Lévy...

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...

transition densities. In the Markov chain setting, one assumes that i1 < ... < in. Then, because of the Markov property, p i 1 , … , i n ( f 1 , … , f...

inequality Doob–Meyer decomposition theorem Local martingale Markov chain Markov property Martingale (betting system) Martingale central limit theorem...

a trivial matter to show that a Gibbs random field satisfies every Markov property. As an example of this fact, see the following: In the image to the...

probability theory, a telescoping Markov chain (TMC) is a vector-valued stochastic process that satisfies a Markov property and admits a hierarchical format...

Ornstein–Uhlenbeck process. Gauss–Markov processes obey Langevin equations. Every Gauss–Markov process X(t) possesses the three following properties: If h(t) is a non-zero...