phase.update {EDISON} | R Documentation |

## Make a network structure or hyperparameter move.

### Description

This function makes a network structure or information sharing hyperparameter move.

### Usage

```
phase.update(Eall, Sall, Ball, Sig2all, X, Y, GLOBvar, HYPERvar, target)
```

### Arguments

`Eall` |
List of changepoints with one entry for each target node. Each entry has length equal to the number of changepoints for that target node. |

`Sall` |
Network structure: List of length equal to the number of target nodes, where each list entry is a NumSegs by NumNodes matrix. |

`Ball` |
Network structure with regression coefficients: Same as Sall, but with regression coefficients as matrix entries. |

`Sig2all` |
Sigma squared. |

`X` |
Input response data. |

`Y` |
Input target data. |

`GLOBvar` |
Global variables used during the MCMC simulation. |

`HYPERvar` |
Hyperparameter variables. |

`target` |
Current target node. |

### Value

Returns a list with the following elements:

`E` |
Changepoints for the current target node. |

`Sall` |
Network structure (possibly updated). |

`Ball` |
Network structure regression coefficients (possibly updated). |

`Sig2all` |
Sigma squared. |

`prior.params` |
Information sharing prior hyperparameters (possibly updated). |

`k` |
Level-2 exponential prior hyperparameter (possibly updated). |

`move` |
Move type: 4 for a network structure move, 5 hyperparameter move. |

`move` |
Structure Move type: 1 for a network structure move, 2 for a level-1 hyperparameter move, 3 for a level-2 hyperparameter move. |

`accept` |
1 if the move has been accepted, 0 otherwise. |

### Author(s)

Sophie Lebre

Frank Dondelinger

### References

For more information on network structure moves and information sharing priors, see:

Dondelinger et al. (2012), "Non-homogeneous dynamic Bayesian networks with Bayesian regularization for inferring gene regulatory networks with gradually time-varying structure", Machine Learning.

### See Also

*EDISON*version 1.1.1 Index]