# Parallel Adaptive Wang-Landau

### Description

Implements the Parallel Adaptive Wang-Landau algorithm.

### Usage

1 |

### Arguments

`target` |
Object of class |

`binning` |
Object of class |

`AP` |
Object of class |

`proposal` |
Object of class |

`verbose` |
Object of class |

### Value

The function returns a list holding various information:

`finalchains` |
The last point of each chain. |

`acceptrates` |
The vector of acceptance rates at each step. |

`sigma` |
The vector of the standard deviations used by the MH kernel along the iterations. If the proposal was adaptive, this allows to check how the adaptation behaved. |

`allchains` |
If asked in the tuning parameters, the chain history. |

`alllogtarget` |
If asked in the tuning parameters, the associated log density evaluations. |

`meanchains` |
If asked in the tuning parameters, the mean (component-wise) of each chain. |

`logthetahistory` |
If asked in the tuning parameters, all the log theta penalties. |

and other quantities, that you can browse by calling `"names(results)"`

where `"results"`

is the output
of the function.

### Author(s)

Luke Bornn <bornn@stat.harvard.edu>, Pierre E. Jacob <pierre.jacob.work@gmail.com>

### See Also

`adaptiveMH, binning`