CortForest-Class {cort}R Documentation

Bagged Cort copulas

Description

CortForest class

Usage

CortForest(
  x,
  p_value_for_dim_red = 0.75,
  n_trees = 10,
  compte_loo_weights = FALSE,
  min_node_size = 1,
  pseudo_data = FALSE,
  number_max_dim = NULL,
  verbose_lvl = 2,
  force_grid = FALSE,
  oob_weighting = TRUE
)

Arguments

x

The data, must be provided as a matrix with each row as an observation.

p_value_for_dim_red

a p_value for the localised dimension reduction test

n_trees

Number of trees

compte_loo_weights

Defaults to FALSE. Allows to use an automatic re-weighting of the trees in the forest, based on leave-one-out considerations.

min_node_size

The minimum number of observation avaliable in a leaf to initialise a split.

pseudo_data

set to True if you are already providing data on the copula space.

number_max_dim

The maximum number of dimension a split occurs in. Defaults to be all of the dimensions.

verbose_lvl

verbosity level : can be 0 (default) or an integer. bigger the integer bigger the output level.

force_grid

boolean (default: FALSE). set to TRUE to force breakpoint to be on the n-checkerboard grid in every tree.

oob_weighting

boolean (default : TRUE) option to weight the trees with an oob criterion (otherwise they are equally weighted)

Details

This class implements the bagging of CORT models, with an out-of-bag error minimisation in the weights.

See O. Laverny, V. Maume-Deschamps, E. Masiello and D. Rullière (2020) for the details of this density estimation procedure, and vignettes(package='cort') for examples of usecases.

Value

An instance of the CortForest S4 class. The object represent the fitted copula and can be used through several methods to query classical (r/d/p/v)Copula methods, constraint influence, etc. Beside returning some inputted parameters, notable slots are :

More details about these slots can be found in the reference.

References

Laverny O, Maume-Deschamps V, Masiello E, Rullière D (2020). “Dependence Structure Estimation Using Copula Recursive Trees.” arXiv preprint arXiv:2005.02912.

Examples

(CortForest(LifeCycleSavings[,1:3],number_max_dim=2,n_trees=2))

[Package cort version 0.3.2 Index]