test_multimod {VALIDICLUST} | R Documentation |
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 thediptest
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)
[Package VALIDICLUST version 0.1.0 Index]