Description Usage Arguments Details Value

Creates a sampler object for a given problem which fits a Bayesian Additive Regreesion Trees model. Internally stores state in such a way as to be mutable.

1 2 3 4 |

`formula` |
An object of class |

`data` |
An optional data frame, list, or environment containing predictors to be used with the
model. For backwards compatibility, can also be the |

`test` |
An optional matrix or data frame with the same number of predictors as |

`subset` |
An optional vector specifying a subset of observations to be used in the fitting process. |

`weights` |
An optional vector of weights to be used in the fitting process. When present, BART
fits a model with observations |

`offset` |
An optional vector specifying an offset from 0 for the relationship between the underyling
function, |

`offset.test` |
The equivalent of |

`verbose` |
A logical determining if additional output is printed to the console. See |

`n.samples` |
A positive integer setting the default number of posterior samples to be returned for each run of
the sampler. Can be overriden at run-time. See |

`tree.prior` |
An expression of the form |

`node.prior` |
An expression of the form |

`resid.prior` |
An expression of the form |

`control` |
An object inheriting from |

`sigma` |
A positive numeric estimate of the residual standard deviation. If |

“Discrete sampler” refers to that `dbarts`

is implemented using ReferenceClasses, so that
there exists a mutable object constructed in C++ that is largely obscured from R. The `dbarts`

function
is the primary way of creating a `dbartsSampler`

, for which a variety of methods
exist.

A reference object of `dbartsSampler`

.

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