piRF (version 0.1.0)

HDI_quantregforest: Implements HDI RF prediction interval method in Zhu 2019. Helper function.

Description

This function implements an HDI RF prediction interval method.

Usage

HDI_quantregforest(
  formula = NULL,
  train_data = NULL,
  test_data = NULL,
  alpha = NULL,
  num_tree = NULL,
  mtry = NULL,
  min_node_size = NULL,
  max_depth = NULL,
  replace = TRUE,
  verbose = FALSE,
  num_threads = NULL
)

Arguments

formula

Object of class formula or character describing the model to fit. Interaction terms supported only for numerical variables.

train_data

Training data of class data.frame, matrix, dgCMatrix (Matrix) or gwaa.data (GenABEL). Matches ranger() requirements.

test_data

Test data of class data.frame, matrix, dgCMatrix (Matrix) or gwaa.data (GenABEL). Utilizes ranger::predict() to get prediction intervals for test data.

alpha

Significance level for prediction intervals.

num_tree

Number of trees.

mtry

Number of variables to randomly select from at each split.

min_node_size

Minimum number of observations before split at a node.

max_depth

maximum depth of each tree in RF. ranger parameter.

replace

Sample with replacement, or not. Utilized for the two different variants outlined in Ghosal, Hooker 2018. Currently variant 2 not implemented.

num_threads

The number of threads to use in parallel. Default is the current number of cores.