Twalk | R Documentation |

T-walk MCMC

Twalk( bayesianSetup, settings = list(iterations = 10000, at = 6, aw = 1.5, pn1 = NULL, Ptrav = 0.4918, Pwalk = 0.4918, Pblow = 0.0082, burnin = 0, thin = 1, startValue = NULL, consoleUpdates = 100, message = TRUE) )

`bayesianSetup` |
Object of class 'bayesianSetup' or 'bayesianOuput'. |

`settings` |
list with parameter values. |

`iterations` |
Number of model evaluations |

`at` |
"traverse" move proposal parameter. Default to 6 |

`aw` |
"walk" move proposal parameter. Default to 1.5 |

`pn1` |
Probability determining the number of parameters that are changed |

`Ptrav` |
Move probability of "traverse" moves, default to 0.4918 |

`Pwalk` |
Move probability of "walk" moves, default to 0.4918 |

`Pblow` |
Move probability of "traverse" moves, default to 0.0082 |

`burnin` |
number of iterations treated as burn-in. These iterations are not recorded in the chain. |

`thin` |
thinning parameter. Determines the interval in which values are recorded. |

`startValue` |
Matrix with start values |

`consoleUpdates` |
Intervall in which the sampling progress is printed to the console |

`message` |
logical determines whether the sampler's progress should be printed |

The probability of "hop" moves is 1 minus the sum of all other probabilities.

Object of class bayesianOutput.

Stefan Paul

Christen, J. Andres, and Colin Fox. "A general purpose sampling algorithm for continuous distributions (the t-walk)." Bayesian Analysis 5.2 (2010): 263-281.

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