test_multimod: Multimodality test for post clustering variable involvement

In benhvt/PCVI: VALID Inference for Clusters Separation Testing

Multimodality test for post clustering variable involvement

Description

Multimodality test for post clustering variable involvement

Usage

test_multimod(X, g, cl, k1, k2)

Arguments

X	The data matrix of size on which the clustering is applied
g	The variable on which the test is applied
cl	The labels of the data obtained thanks to a clustering algorithm
k1	The first cluster of interest
k2	The second cluster of interest

Value

A list containing : A list with the following elements

• data_for_test : The data used for the test

• stat_g : The dip statistic

• pval : The resulting p-values of the test computed with the diptest function

Examples

X <- matrix(rnorm(200),ncol = 2)
hcl_fun <- function(x){
return(as.factor(cutree(hclust(dist(x), method = "ward.D2"), k=2)))}
cl <- hcl_fun(X)
plot(X, col=cl)
test_var1 <- test_multimod(X, g=1, k1=1, k2=2, cl = cl)
test_var2 <- test_multimod(X, g=2, k1=1, k2=2, cl = cl)

benhvt/PCVI documentation built on Dec. 2, 2022, 10:47 p.m.