Back Markov-eienskap Afrikaans خاصية ماركوف Arabic Марковско свойство Bulgarian Propietat de Màrkov Catalan Markow-Eigenschaft German Propiedad de Márkov Spanish خاصیت مارکوف Persian Propriété de Markov French Markovljevo svojstvo Croatian Proprietà di Markov Italian
In probability theory and statistics, the term Markov property refers to the memoryless property of a stochastic process, which means that its future evolution is independent of its history. It is named after the Russian mathematician Andrey Markov.[1] The term strong Markov property is similar to the Markov property, except that the meaning of "present" is defined in terms of a random variable known as a stopping time.
The term Markov assumption is used to describe a model where the Markov property is assumed to hold, such as a hidden Markov model.
A Markov random field extends this property to two or more dimensions or to random variables defined for an interconnected network of items.[2] An example of a model for such a field is the Ising model.
A discrete-time stochastic process satisfying the Markov property is known as a Markov chain.
- ^ Markov, A. A. (1954). Theory of Algorithms. [Translated by Jacques J. Schorr-Kon and PST staff] Imprint Moscow, Academy of Sciences of the USSR, 1954 [Jerusalem, Israel Program for Scientific Translations, 1961; available from Office of Technical Services, United States Department of Commerce] Added t.p. in Russian Translation of Works of the Mathematical Institute, Academy of Sciences of the USSR, v. 42. Original title: Teoriya algorifmov. [QA248.M2943 Dartmouth College library. U.S. Dept. of Commerce, Office of Technical Services, number OTS 60-51085.]
- ^ Dodge, Yadolah. (2006) The Oxford Dictionary of Statistical Terms, Oxford University Press. ISBN 0-19-850994-4
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