# Markov model

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Related to Markov model: Markov process, Hidden Markov model

## Markov model

A model used in decision analysis for evaluating potential outcomes of a disease process, which are defined as specific health states, transitions among which are modelled iteratively. In standard decision tree analysis, a patient moves through states—for example, from not treated, to treated, to final outcome; in a Markov process, a patient moves between states (e.g., backwards and forward between continuous ambulatory peritoneal dialysis and haemodialysis). Some states cannot be left once entered (so-called “absorbing states”), including death.

## Markov chain, Markov model

a mathematical model that makes it possible to study complex systems by establishing a state of the system and then effecting a transition to a new state, such a transition being dependent only on the values of the current state, and not dependent on the previous history of the system up to that point.
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Our Markov model clearly showed cost-effectiveness since there was a 99% chance of an additional cost of SNM when compared with OMT; our threshold was less than 50 000 per unit increase in QALY during the 5 year period (Fig.
First, a key Markov model assumption is that the functional level to which a subject moves in a given year depends only on his or her functional level the previous year, not on prior years.
We present a novel approach for session separation using a trained first-order Markov model to facilitate session separation.
2] Murugesan N and Suguna P, Optimization of a Hidden Markov Model using Gaines construction of Probabilistic Finite State Automata, International Conference on Mathematics and Computer Science, Loyola College, Chennai, India, July, 2008.
Through our research for finding different ways of doing the loose matching, we have found that the best matching approach for our problem is Hidden Markov Models.
This Poisson-like limit has been observed for occurrences of one word by Regnier and Szpankowski [18] in the Bernoulli and Markov models; we conjecture the same result for the count of clumps of one word for rare words in the Markov model.
If a Markov model has the property that a bank starting in any category has a positive probability of moving to any other size category in a finite number of periods, then several useful theorems apply.
One key feature of the estimated Markov model is that once the economy enters the ordinary growth state, it cannot return directly to the snap-back state.
Estimated timing of mother-to-child human immunodeficiency virus type I (HIV-1) transmission by use era of a Markov model.
Mills (1999) describes the two-state Markov model as a type of "switching- regime" model based on an autoregressive-moving average process, capable of handling asymmetry and conditional heteroskedasticity.

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