# plot.clustEff: Plot Clustering Effects In clustEff: Clusters of Effects Curves in Quantile Regression Models

 plot.clustEff R Documentation

## Plot Clustering Effects

### Description

Produces a dendrogram, a cluster plot and a boxplot of average distance cluster of an object of class “`clustEff`”.

### Usage

```## S3 method for class 'clustEff'
plot(x, xvar=c("clusters", "dendrogram", "boxplot", "numclust"), which,
polygon=TRUE, dissimilarity=TRUE, par=FALSE, ...)
```

### Arguments

 `x` An object of class “`clustEdd`”, typically the result of a call to `clustEff`. `xvar` Clusters: plot of the k clusters; Dendrogram: plot of the tree after computing the dissimilarity measure and applying a hierarchical clustering algorithm; Boxplot: plot the average distance within clusters; Numclust: plot the curve to minimize to select the best number of clusters; `which` If missing all curves effect are plotted. `polygon` If TRUE confidence intervals are represented by shaded areas via polygon. Otherwise, dashed lines are used. If NULL no confidence intervals are represented `dissimilarity` If TRUE dissimilarity measure within each cluster is used to do boxplot representation. `par` If TRUE the screen is automaticcaly splitted. `...` additional graphical parameters, that can include xlim, ylim, xlab, ylab, col, lwd, lty. See `par`.

### Details

Different plot for the clustering algorithm.

### Author(s)

Gianluca Sottile gianluca.sottile@unipa.ot

`clustEff` for cluster algorithm; `extract.object` for extracting information through a quantile regression coefficient modeling in a multivariate case; `summary.clustEff` for clustering summary.

### Examples

```
# using simulated data

# see the documentation for 'clustEff'

```

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