Description Usage Arguments Details Value Author(s) See Also

View source: R/preexploration.R

This function takes a target distribution, an integer representing the number of parallel chains, and an integer representing a number of iterations, and runs adaptive Metropolis-Hastings algorithm using them. The chains are then used to create a range called SuggestedRange, to be used to bin the state space according to the energy levels. The energy is here defined as minus the log density of the target distribution.

1 | ```
preexplorationAMH(target, nchains, niterations, proposal, verbose)
``` |

`target` |
Object of class |

`nchains` |
Object of class |

`niterations` |
Object of class |

`proposal` |
Object of class |

`verbose` |
Object of class |

The adaptive Metropolis-Hastings algorithm used in the function is described in more details
in the help page of `adaptiveMH`

The function returns a list holding the following entries:

`LogEnergyRange` |
This holds the minimum and maximum energy values seen by the chains during the exploration. |

`LogEnergyQtile` |
Returns the first 10% quantile of the energy values seen by the chains during the exploration. |

`SuggestedRange` |
This holds the suggested range, that is, the first 10% quantile and the maximum value
of the energy values seen during the exploration. This can be passed as the |

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

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

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