CHMM_VEM {CHMM} | R Documentation |

## Perform variational inference of coupled Hidden Markov Models.

### Description

Perform variational inference of coupled Hidden Markov Models.

### Usage

```
CHMM_VEM(X, nb.states, S = NULL, omega = 0.7, meth.init = "mclust",
var.equal = TRUE, itmax = 500, threshold = 1e-07)
```

### Arguments

`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. |

### Value

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.

### References

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.

*CHMM*version 0.1.1 Index]