The univariate HMM object is output of the function `callPeaksUnivariate`

and is a `list()`

with various entries. The `class()`

attribute of this list was set to "uniHMM". For a given hmm, the entries can be accessed with the list operators 'hmm[[]]' or 'hmm$'.

A `list()`

with the following entries:

`info` |
Experiment table for this object. |

`bincounts` |
A |

`bins` |
A |

`peaks` |
A |

`weights` |
Weight for each component. Same as |

`transitionProbs` |
Matrix of transition probabilities from each state (row) into each state (column). |

`transitionProbs.initial` |
Initial |

`startProbs` |
Probabilities for the first bin. Same as |

`startProbs.initial` |
Initial |

`distributions` |
Estimated parameters of the emission distributions. |

`distributions.initial` |
Distribution parameters at the beginning of the Baum-Welch. |

`post.cutoff` |
Cutoff for posterior probabilities to call peaks. |

`convergenceInfo` |
Contains information about the convergence of the Baum-Welch algorithm. |

`convergenceInfo$eps` |
Convergence threshold for the Baum-Welch. |

`convergenceInfo$loglik` |
Final loglikelihood after the last iteration. |

`convergenceInfo$loglik.delta` |
Change in loglikelihood after the last iteration (should be smaller than |

`convergenceInfo$num.iterations` |
Number of iterations that the Baum-Welch needed to converge to the desired |

`convergenceInfo$time.sec` |
Time in seconds that the Baum-Welch needed to converge to the desired |

`convergenceInfo$max.mean` |
Value of parameter |

`convergenceInfo$read.cutoff` |
Cutoff value for read counts. |

`callPeaksUnivariate`

, `multiHMM`

, `combinedMultiHMM`

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