FADPplot: Visualize the result of FADPclust

In FADPclust: Functional Data Clustering Using Adaptive Density Peak Detection

Visualize the result of FADPclust

Description

Plot the f vs delta plot with selected centroids.

Usage

FADPplot(object, cols = "default")

Arguments

object	object of class 'FADPclust' that is returned from FADPclust().
cols	vector of colors used to distinguish different clusters. Ten default colors are given.

See Also

FADPclust, FADPsummary.

Examples

###univariate functional data
data("simData1")
plot(simData1, xlab = "x", ylab = "y")
FADP1.ans <- FADPclust(fdata = simData1, cluster = 2:5, method = "FADP1",
                       proportion = seq(0.02, 0.2, 0.02), f.cut = 0.15,
                       stats = "Avg.silhouette")
FADPsummary(FADP1.ans); FADPplot(FADP1.ans)

FADP2.ans <- FADPclust(fdata = simData1, cluster = 2:5, method = "FADP2",
                       proportion = seq(0.02, 0.2, 0.02), f.cut = 0.15,
                       pve = 0.9, stats = "Avg.silhouette")
FADPsummary(FADP2.ans); FADPplot(FADP2.ans)

###multivariate functional data
data("simData2")
FADP1.ans <- FADPclust(fdata = simData2, cluster = 2:5, method = "FADP1",
                       proportion = seq(0.02, 0.2, 0.02), f.cut = 0.15,
                       pve = 0.9, stats = "Avg.silhouette")
FADPsummary(FADP1.ans); FADPplot(FADP1.ans)

FADP2.ans <- FADPclust(fdata = simData2, cluster = 2:5, method = "FADP2",
                       proportion = seq(0.02, 0.2, 0.02), f.cut = 0.15,
                       pve = 0.9, stats = "Avg.silhouette")
FADPsummary(FADP2.ans); FADPplot(FADP2.ans)

FADPclust documentation built on Nov. 10, 2022, 5:52 p.m.