classifier_test: Classifier k-sample test

In HectorRDB/Ecume: Equality of 2 (or k) Continuous Univariate and Multivariate Distributions

Classifier k-sample test

Description

Classifier k-sample test

Usage

classifier_test(
  x,
  y,
  split = 0.7,
  thresh = 0,
  method = "knn",
  control = caret::trainControl(method = "cv"),
  ...
)

Arguments

x	Samples from the first distribution or a list of samples from k distribution
y	Samples from the second distribution. Only used if x is a vector.
split	How to split the data between training and test. Default to .7
thresh	Value to add to the null hypothesis. See details.
method	Which model(s) to use during training. Default to knn.
control	Control parameters when fitting the methods. See trainControl
...	Other parameters passed to train

Details

See Lopez-Paz et .al for more background on those tests.

Value

A list containing the following components:

• statistic the value of the test statistic.

• p.value the p-value of the test.

References

Lopez-Paz, D., & Oquab, M. (2016). Revisiting Classifier Two-Sample Tests, 1–15. Retrieved from http://arxiv.org/abs/1610.06545

Examples

 x <- matrix(c(runif(100, 0, 1),
               runif(100, -1, 1)),
             ncol = 2)
 y <- matrix(c(runif(100, 0, 3),
               runif(100, -1, 1)),
             ncol = 2)
 classifier_test(x, y)

HectorRDB/Ecume documentation built on June 21, 2022, 7:13 a.m.