Description Usage Arguments Value References

Perform variational inference of coupled Hidden Markov Models.

1 2 |

`X` |
a data matrix of observations. Columns correspond to individuals. |

`nb.states` |
a integer specifying the numbers of states. |

`S` |
a matrix of similarity between individuals. |

`omega` |
a value of omega. |

`meth.init` |
a string specifying the initialization method ("mclust" or "kmeans"). The default method is "mclust". |

`var.equal` |
a logical variable indicating whether to treat the variances as being equal. |

`itmax` |
an integer specifying the maximal number of iterations for the EM algorithm. |

`threshold` |
a value for the threshold used for the stopping criteria. |

a list of 9 components

`postPr`

a list containing for each series the posterior probabilities.

`initPr`

a numeric specifying the initial state probabilities.

`transPr`

a matrix of the state transition probabilities.

`esAvg`

a numeric of the estimated mean for each state.

`esVar`

a numeric of the estimated variance for each state.

`emisPr`

a list containing for each series the emission probabilities.

`emisPrW`

a list containing for each series the emission probabilities taking into account for the dependency structure.

`RSS`

a numeric corresponding to the Residuals Sum of Squares.

`iterstop`

an integer corresponding to the total number of iterations.

Wang, X., Lebarbier, E., Aubert, J. and Robin, S., Variational inference for coupled Hidden Markov Models applied to the joint detection of copy number variations.

Embedding an R snippet on your website

Add the following code to your website.

For more information on customizing the embed code, read Embedding Snippets.