extree_data | R Documentation |

A routine for preprocessing data before an extensible tree can be grown by
`extree_fit`

.

extree_data(formula, data, subset, na.action = na.pass, weights, offset, cluster, strata, scores = NULL, yx = c("none", "matrix"), ytype = c("vector", "data.frame", "matrix"), nmax = c(yx = Inf, z = Inf), ...)

`formula` |
a formula describing the model of the form |

`data` |
an optional data.frame containing the variables in the model. |

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

`na.action` |
a function which indicates what should happen when the data contain missing values. |

`weights` |
an optional vector of weights. |

`offset` |
an optional offset vector. |

`cluster` |
an optional factor describing clusters. The interpretation depends on the specific tree algorithm. |

`strata` |
an optional factor describing strata. The interpretation depends on the specific tree algorithm. |

`scores` |
an optional named list of numeric scores to be assigned to
ordered factors in the |

`yx` |
a character indicating if design matrices shall be computed. |

`ytype` |
a character indicating how response variables shall be stored. |

`nmax` |
a numeric vector of length two with the maximal number of
bins in the response and |

`...` |
additional arguments. |

This internal functionality will be the basis of implementations of other
tree algorithms in future versions. Currently, only `ctree`

relies on
this function.

An object of class `extree_data`

.

data("iris") ed <- extree_data(Species ~ Sepal.Width + Sepal.Length | Petal.Width + Petal.Length, data = iris, nmax = c("yx" = 25, "z" = 10), yx = "matrix") ### the model.frame mf <- model.frame(ed) all.equal(mf, iris[, names(mf)]) ### binned y ~ x part model.frame(ed, yxonly = TRUE) ### binned Petal.Width ed[[4, type = "index"]] ### response ed$yx$y ### model matrix ed$yx$x

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