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In probability theory, a Markov process is a stochastic process that has the Markov property. Wikipedia does not have an article with this exact name. ... In probability theory, a stochastic process has the Markov property if the conditional probability distribution of future states of the process, given the present state, depends only upon the current state, i. ... It has been suggested that this article or section be merged with Probability axioms. ... In the mathematics of probability, a stochastic process is a random function. ... In probability theory, a stochastic process has the Markov property if the conditional probability distribution of future states of the process, given the present state, depends only upon the current state, i. ...

Often, the term Markov chain is used to mean a discrete-time Markov process. Also see continuous-time Markov process. In mathematics, a Markov chain, named after Andrey Markov, is a discrete-time stochastic process with the Markov property. ... In probability theory, a continuous-time Markov process is a stochastic process { X(t) : t ≥ 0 } that enjoys the Markov property and takes values from amongst the elements of a discrete set called the state space. ...

See also

• Markov chain
• Shift of finite type
• Markov decision process
• Semi-Markov process
• Continuous-time Markov process
• Variable-order Markov model

In mathematics, a Markov chain, named after Andrey Markov, is a discrete-time stochastic process with the Markov property. ... In mathematics, subshifts of finite type are used to model dynamical systems, and in particular are the objects of study in symbolic dynamics and ergodic theory. ... To meet Wikipedias quality standards, this article or section may require cleanup. ... A semi-Markov process is one that, when it enters state i, spends a random time having distribution and mean in that state before making a transition. ... In probability theory, a continuous-time Markov process is a stochastic process { X(t) : t ≥ 0 } that enjoys the Markov property and takes values from amongst the elements of a discrete set called the state space. ... Variable-order Markov (VOM) models are an important class of models that extend the well known Markov chain models. ...

External Links

Markov process from MathWorld

References

• P-E E. Bergner, Dynamics of Markovian Particles; A kinetics of macroscopic particles in open heterogeneous systems , (2005)