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  2. Markov model - Wikipedia

    en.wikipedia.org/wiki/Markov_model

    For example, a series of simple observations, such as a person's location in a room, can be interpreted to determine more complex information, such as in what task or activity the person is performing. Two kinds of Hierarchical Markov Models are the Hierarchical hidden Markov model [2] and the Abstract Hidden Markov Model. [3]

  3. Markov property - Wikipedia

    en.wikipedia.org/wiki/Markov_property

    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. [1] An example of a model for such a field is the Ising model. A discrete ...

  4. Examples of Markov chains - Wikipedia

    en.wikipedia.org/wiki/Examples_of_Markov_chains

    A game of snakes and ladders or any other game whose moves are determined entirely by dice is a Markov chain, indeed, an absorbing Markov chain. This is in contrast to card games such as blackjack, where the cards represent a 'memory' of the past moves. To see the difference, consider the probability for a certain event in the game.

  5. Hidden Markov random field - Wikipedia

    en.wikipedia.org/wiki/Hidden_Markov_random_field

    The main difference with a hidden Markov model is that neighborhood is not defined in 1 dimension but within a network, i.e. is allowed to have more than the two neighbors that it would have in a Markov chain. The model is formulated in such a way that given , are independent (conditional independence of the observable variables given the ...

  6. Hidden Markov model - Wikipedia

    en.wikipedia.org/wiki/Hidden_Markov_model

    Figure 1. Probabilistic parameters of a hidden Markov model (example) X — states y — possible observations a — state transition probabilities b — output probabilities. In its discrete form, a hidden Markov process can be visualized as a generalization of the urn problem with replacement (where each item from the urn is returned to the original urn before the next step). [7]

  7. Markov renewal process - Wikipedia

    en.wikipedia.org/wiki/Markov_renewal_process

    [1] [2] [3] (See also: hidden semi-Markov model.) A semi-Markov process (defined in the above bullet point) in which all the holding times are exponentially distributed is called a continuous-time Markov chain. In other words, if the inter-arrival times are exponentially distributed and if the waiting time in a state and the next state reached ...

  8. Variable-order Markov model - Wikipedia

    en.wikipedia.org/wiki/Variable-order_Markov_model

    In the mathematical theory of stochastic processes, variable-order Markov (VOM) models are an important class of models that extend the well known Markov chain models. In contrast to the Markov chain models, where each random variable in a sequence with a Markov property depends on a fixed number of random variables, in VOM models this number of conditioning random variables may vary based on ...

  9. Model-based testing - Wikipedia

    en.wikipedia.org/wiki/Model-based_testing

    A model describing a SUT is usually an abstract, partial presentation of the SUT's desired behavior. Test cases derived from such a model are functional tests on the same level of abstraction as the model. These test cases are collectively known as an abstract test suite. An abstract test suite cannot be directly executed against an SUT because ...

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