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Markov Chain
(redirected from Transition probabilities)

   Also found in: Dictionary/thesaurus, Medical, Wikipedia 0.01 sec.
Markov chain [′mar‚kȯf ‚chān]
(mathematics)
A Markov process whose state space is finite or countably infinite.

(probability)Markov chain - (Named after Andrei Markov) A model of sequences of events where the probability of an event occurring depends upon the fact that a preceding event occurred.

A Markov process is governed by a Markov chain.

In simulation, the principle of the Markov chain is applied to the selection of samples from a probability density function to be applied to the model. Simscript II.5 uses this approach for some modelling functions.


Markov Chain 

a concept in probability theory that emerged from the works of the Russian mathematician A. A. Markov (the elder) that dealt with the study of sequences of dependent trials and sums of random variables associated with them. The development of the theory of Markov chains facilitated the creation of the general theory of Markov processes.



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Using this algorithm, Equation (29) becomes: [MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII] (35) Obviously, we do not have the transition probabilities in it.
These were parameterized by a series of model states (locations in the estuary or ocean where migratory striped bass could occur) connected by transition probabilities (rates at which striped bass may move between these geographic locations).
Namely, a program module could be derived from basic tagger function set, using tagger's tag transition probabilities matrix to find the optimal tag sequence in the search space, narrowed by using output of the inflectional lexicon instead of a generally poor lexical database stored in the emission probability matrix acquired at training.
 
 
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