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Dan aka jack (talk | contribs) m →Markov chain: adding an 'a' |
Marginally improve the introduction with some material from Markov property |
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{{context|date=December 2011}}{{expert-subject|date=January 2013}}
In [[probability theory]], a '''Markov model''' is a [[stochastic model]] that assumes the [[Markov property]]. A stochastic model models a process where the state depends on previous states in a non-deterministic way. A stochastic process has the Markov property if the [[conditional probability distribution]] of future states of the process (conditional on both past and present values) depends only upon the present state; that is, given the present, the future does not depend on the past. Generally, this assumption enables reasoning and computation with the model that would otherwise be [[Intractability (complexity)|intractable]].
==Introduction==
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