summary.clustEff: Summary clustEff algorithm

In clustEff: Clusters of Effects Curves in Quantile Regression Models

Summary clustEff algorithm

Description

Summary of an object of class “clustEff”.

Usage

## S3 method for class 'clustEff'
summary(object, ...)

Arguments

object	An object of class “clustEff”, the result of a call to clustEff.
...	for future methods.

Details

A summary of the clustering algorithm is printed.

Value

The following items is returned:

k	The number of selected clusters.
n	The number of observations.
p	The number of curves.
step	The selected step for computing the dissimilarity matrix.
alpha	The alpha-percentile used for computing the dissimilarity matrix.
method	The selected method to compute the hierarchical cluster analysis.
cut.method	The selected method to choose the best number of clusters.
tabClust	The table of clusters.
avClust	The average distance within clusters.
avSilhouette	Silhouette widths for clusters.
avDiss	The average dissimilarity measure within clusters.

Author(s)

Gianluca Sottile [e-mail]

See Also

clustEff, for cluster algorithmextract.object for extracting information through a quantile regression coefficient modeling in a multivariate case and plotting objects of class “clustEff”.

Examples

# using simulated data

# see the documentation for 'clustEff'

clustEff documentation built on June 28, 2022, 5:06 p.m.