FR.test: Friedman-Rafsky (FR) test
In MD2sample: Various Methods for the Two Sample Problem in D>1 Dimensions

FR.test

R Documentation

Friedman-Rafsky (FR) test

Description

FR test is a multivariate generalization of nonparametric two-sample test. This function is an implementation with customized options, including a visualization of the minimum spanning tree (MST).

Usage

FR.test(
  samp1,
  samp2,
  use.cosine = FALSE,
  binary = FALSE,
  binary.cutoff = 2,
  plot.MST = FALSE,
  col = c("#F0E442", "#56B4E9"),
  label.names = c("Sample 1", "Sample 2"),
  vertex.size = 5,
  edge.width = 1,
  ...
)

Arguments

`samp1`	Numeric matrix or data frame for Sample 1. Rows are multivariate dimensions, and columns are samples. E.g. gene by cell.
`samp2`	Numeric matrix or data frame for Sample 2.
`use.cosine`	An option if to use cosine distance. Logical variable. By default (`FALSE`), Euclidean distance is used.
`binary`	An option if to use binary values. Logical variable. Default: `FALSE`. If `TRUE`, use `binary.cutoff` to dichotomize `samp1` and `samp2`.
`binary.cutoff`	Numeric value for binary cutoff. Binary value = 1 if greater than `binary.cutoff`, 0 otherwise. Default: `2`.
`plot.MST`	Boolean variable indicating if to plot the minimum spanning tree (MST). Default: `FALSE`.
`col`	Character vector of length two for customized colors of the nodes in MST. Default: `c("#F0E442", "#56B4E9")`.
`label.names`	Character vector of length two for customized names of the two samples. Default: `c("Sample 1","Sample 2")`.
`vertex.size`, `edge.width`, `...`	Additional plotting parammeters passed to `plot.igraph`. Default: `vertex.size=5, edge.width=1`.

Value

Test statistics and p-values.

`runs`	Total number of subtrees.
`runs.samp1`	Number of subtrees of Sample 1.
`runs.samp2`	Number of subtrees of Sample 2.
`stat`	The standardized FR statistic.
`p.value`	P-value of the FR test.