randIndFx: Distance of categorical data (Jaccard, Rand and adjusted Rand...

In wrMisc: Analyze Experimental High-Throughput (Omics) Data

Distance of categorical data (Jaccard, Rand and adjusted Rand index)

Description

randIndFx calculates distance of categorical data (as Rand Index, Adjusted Rand Index or Jaccard Index). Note: uses/requires package flexclust Methods so far available (via flexclust): "ARI" .. adjusted Rand Index, "RI" .. Rand index, "J" .. Jaccard, "FM" .. Fowlkes-Mallows.

Usage

randIndFx(ma, method = "ARI", adjSense = TRUE, silent = FALSE, callFrom = NULL)

Arguments

ma	(matrix) main input for distance calulation
method	(character) name of distance method (eg "ARI","RI","J","FM")
adjSense	(logical) allows introducing correlation/anticorrelation (interprete neg distance results as anti)
silent	(logical) suppres messages
callFrom	(character) allow easier tracking of messages produced

Value

This function returns a distance matrix

See Also

comPart in randIndex

Examples

set.seed(2016); tab2 <- matrix(sample(1:2, size=42, replace=TRUE), ncol=7)
if(requireNamespace("flexclust")) { flexclust::comPart(tab2[1,], tab2[2,])
  flexclust::comPart(tab2[1,], tab2[3,])
  flexclust::comPart(tab2[1,], tab2[4,]) }
## via randIndFx():
  randIndFx(tab2, adjSense=FALSE)
  cor(t(tab2))
  randIndFx(tab2, adjSense=TRUE)

wrMisc documentation built on Nov. 17, 2023, 5:09 p.m.