varclust: Clustering of numeric variables

In mbgraphic: Measure Based Graphic Selection

Description

The function clusters variables using the average linkage algorithm.

Usage

varclust(data, c = NULL, mincor = NULL)

Arguments

data	A data frame.
c	A positive integer. The number of clusters.
mincor	Numeric. The minimal correlation within each of the single clusters.

Details

The number of clusters can be set by specifying c or choosing mincor (but not both at the same time). If mincor is used, the number of clusters is defined by a minimum correlation. That means every single pair of variables in the individual clusters is correlated with a value which is at least mincor.

Value

A list with the following object:

c	The number of clusters.
mincor	The minimal correlation within each of the single clusters.
clusters	The cluster allocation for each variable.
clusrep	A character vector indicating the variables which are used as representatives for the clusters.
dfclusrep	A data frame which only holds the cluster representatives as variables.

Author(s)

Katrin Grimm

Examples

data(Election2005)
## Not run: 
# Variable clustering based on minimum correlation
vc1 <- varclust(Election2005,mincor=0.8)
vc1$c # The number of clusters is 45

# Variable clustering based on the number of clusters
vc2 <- varclust(Election2005,30)
vc2$mincor # The minimum correlation is 0.63

## End(Not run)

mbgraphic documentation built on May 2, 2019, 2:45 a.m.