Type: Package
Title: Random Forest Two-Sample Tests
Version: 1.0.1
Description: An implementation of Random Forest-based two-sample tests as introduced in Hediger & Michel & Naef (2022).
License: GPL-3
Imports: stats, ranger
Encoding: UTF-8
Suggests: testthat
RoxygenNote: 7.3.2
NeedsCompilation: no
Packaged: 2024-09-23 19:50:46 UTC; Simon Hediger
Author: Simon Hediger [aut, cre], Loris Michel [aut], Jeffrey Naef [aut]
Maintainer: Simon Hediger <simon.hediger@uzh.ch>
Repository: CRAN
Date/Publication: 2024-09-23 22:00:08 UTC

HypoRF; a Random Forest based Two Sample Test

Description

Performs a permutation two sample test based on the out-of-bag-error of random forest.

Usage

hypoRF(
  data1,
  data2,
  K = 100,
  statistic = "PerClassOOB",
  normalapprox = F,
  seed = NULL,
  alpha = 0.05,
  ...
)

Arguments

data1

An object of type "data.frame". The first sample.

data2

An object of type "data.frame". The second sample.

K

A numeric value specifying the number of times the created label is permuted. For K = 1 a binomial test is carried out. The Default is K = 100.

statistic

A character value specifying the statistic for permutation testing. Two options available

  • PerClassOOB Sum of OOB per class errors.

  • OverallOOB OOB-error.

. Default is statistic = "PerClassOOB".

normalapprox

A logical value asking for the use of a normal approximation. Default is normalapprox = FALSE.

seed

A numeric value for reproducibility.

alpha

The level of the test. Default is alpha = 0.05.

...

Arguments to be passed to ranger

Value

A list with elements

See Also

ranger

Examples

# Using the default testing procedure (permutation test)
x1 <- data.frame(x=stats::rt(50, df=1.5))
x2 <- data.frame(x=stats::rnorm(50))
hypoRF(x1, x2, num.trees = 50)
# Using the exact binomial test
hypoRF(x1, x2, K=1)