Description Objects from the Class Slots Methods Author(s) See Also Examples

Virtual base class for HMMs.

Do not create objects of this class directly. Instead use objects of derived classes like
`"contHMM"`

.

`transition.matrix`

:Object of class

`"matrix"`

, storing the transition probabilities of the Markov chain.`emission`

:Object of class

`"list"`

containing objects of class`"dist"`

to represent emission distributions for each state.`init`

:Object of class

`"numeric"`

. The initial state distribution of the Markov chain.

- baumWelch
`signature(hmm = "hmm", obs = "list")`

: Baum-Welch algorithm to estimate model parameters.- viterbiTraining
`signature(hmm = "hmm", obs = "list")`

: Viterbi training to estimate model parameters.- viterbi
`signature(hmm = "hmm")`

: Viterbi algorithm to calculate most likely state sequence.- backward
`signature(hmm = "hmm")`

: Computing of backward variables.- forward
`signature(hmm = "hmm")`

: Computing of forward variables.- states
`signature(hmm = "hmm")`

: Returns state names.- show
`signature(object = "hmm")`

: Print summary of hmm object.

Peter Humburg

`contHMM`

, `baumWelch`

, `viterbiTraining`

,
`viterbi`

, `forward`

, `backward`

, `states`

1 | ```
showClass("hmm")
``` |

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