plotDensityClust {densityClust}

Plot densityCluster results

Description

Generate a single panel of up to three diagnostic plots for a densityClust object.

Usage

plotDensityClust(
  x,
  type = "all",
  n = 20,
  mds = NULL,
  dim.x = 1,
  dim.y = 2,
  col = NULL,
  alpha = 0.8
)

Arguments

x

A densityCluster object as produced by densityClust

type

A character vector designating which figures to produce. Valid options include "dg" for a decision graph of \delta vs. \rho, "gg" for a gamma graph depicting the decrease of \gamma (= \delta * \rho) across samples, and "mds", for a Multi-Dimensional Scaling (MDS) plot of observations. Any combination of these three can be included in the vector, or to produce all plots, specify type = "all".

n

Number of observations to plot in the gamma graph.

mds

A matrix of scores for observations from a Principal Components Analysis or MDS. If omitted, and a MDS plot has been requested, one will be calculated.

dim.x, dim.y

The numbers of the dimensions to plot on the x and y axes of the MDS plot.

col

Vector of colors for clusters.

alpha

Value in 0:1 controlling transparency of points in the decision graph and MDS plot.

Value

A panel of the figures specified in type are produced. If designated, clusters are color-coded and labelled. If present in x, the rho and delta thresholds are designated in the decision graph by a set of solid black lines.

Author(s)

Eric Archer [e-mail]

Examples

data(iris)
data.dist <- dist(iris[, 1:4])
pca <- princomp(iris[, 1:4])

# Run initial density clustering
dens.clust <- densityClust(data.dist)
op <- par(ask = TRUE)

# Show the decision graph
plotDensityClust(dens.clust, type = "dg")

# Show the decision graph and the gamma graph
plotDensityClust(dens.clust, type = c("dg", "gg"))

# Cluster based on rho and delta
new.clust <- findClusters(dens.clust, rho = 4, delta = 2)

# Show all graphs with clustering
plotDensityClust(new.clust, mds = pca$scores)

par(op)