.dcFit | R Documentation |

This is the workhorse for `dc.fit`

and
`dc.parfit`

.

.dcFit(data, params, model, inits, n.clones, multiply = NULL, unchanged = NULL, update = NULL, updatefun = NULL, initsfun = NULL, flavour = c("jags", "bugs", "stan"), n.chains=3, cl = NULL, parchains = FALSE, return.all=FALSE, check.nclones=TRUE, ...)

`data` |
A named list (or environment) containing the data. |

`params` |
Character vector of parameters to be sampled. It can be a list of 2 vectors, 1st element is used as parameters to monitor, the 2nd is used as parameters to use in calculating the data cloning diagnostics. |

`model` |
Character string (name of the model file), a function containing
the model, or a |

`inits` |
Optional specification of initial values in the form of a list or a
function (see Initialization at |

`n.clones` |
An integer vector containing the numbers of clones to use iteratively. |

`multiply` |
Numeric or character index for list element(s) in the |

`unchanged` |
Numeric or character index for list element(s) in the |

`update` |
Numeric or character index for list element(s) in the |

`updatefun` |
A function to use for updating |

`initsfun` |
A function to use for generating initial values, |

`flavour` |
If |

`n.chains` |
Number of chains to generate. |

`cl` |
A cluster object created by |

`parchains` |
Logical, whether parallel chains should be run. |

`return.all` |
Logical. If |

`check.nclones` |
Logical, whether to check and ensure that values of |

`...` |
Other values supplied to |

An object inheriting from the class 'mcmc.list'.

Peter Solymos, solymos@ualberta.ca, implementation is based on many discussions with Khurram Nadeem and Subhash Lele.

`dc.fit`

, `dc.parfit`

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