Description Usage Arguments Value Author(s) Examples

Make all conditional inference trees

1 2 3 4 5 6 7 8 | ```
create_ctree(
given_ind,
x_train,
mincriterion,
minsplit,
minbucket,
use_partykit = "on_error"
)
``` |

`given_ind` |
Numeric value. Indicates which features are conditioned on. |

`x_train` |
Numeric vector. Indicates the specific values of features for individual i. |

`mincriterion` |
Numeric value or vector equal to 1 - alpha where alpha is the nominal level of the conditional independence tests. Can also be a vector equal to the length of the number of features indicating which mincriterion to use when conditioning on various numbers of features. |

`minsplit` |
Numeric value. Equal to the value that the sum of the left and right daughter nodes need to exceed. |

`minbucket` |
Numeric value. Equal to the minimum sum of weights in a terminal node. |

`use_partykit` |
String. In some semi-rare cases |

List with conditional inference tree and the variables conditioned/not conditioned on.

Annabelle Redelmeier, Martin Jullum

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 | ```
if (requireNamespace("MASS", quietly = TRUE) & requireNamespace("party", quietly = TRUE)) {
m <- 10
n <- 40
n_samples <- 50
mu <- rep(1, m)
cov_mat <- cov(matrix(rnorm(n * m), n, m))
x_train <- data.table::data.table(MASS::mvrnorm(n, mu, cov_mat))
given_ind <- c(4, 7)
mincriterion <- 0.95
minsplit <- 20
minbucket <- 7
sample <- TRUE
create_ctree(
given_ind = given_ind, x_train = x_train,
mincriterion = mincriterion, minsplit = minsplit,
minbucket = minbucket, use_partykit = "on_error"
)
}
``` |

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