Robust Trimmed Clustering

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Documentation for package ‘tclust’ version 2.1-2

• DESCRIPTION file.
• User guides, package vignettes and other documentation.

Help Pages

ctlcurves	Classification Trimmed Likelihood Curves
DiscrFact	Discriminant Factor analysis for 'tclust' objects
estepRR	Function to perform the E-step for a Gaussian mixture distribution
flea	Flea
geyser2	Old Faithful Geyser Data
LG5data	LG5data data
M5data	M5data data
pine	Pinus nigra dataset
plot.ctlcurves	The 'plot' method for objects of class 'ctlcurves'
plot.DiscrFact	The 'plot' method for objects of class 'DiscrFact'
plot.rlg	Plot an 'rlg' object
plot.tclust	Plot Method for 'tclust' and 'tkmeans' Objects
plot.tclustIC	The 'plot' method for objects of class 'tclustIC'
plot.tkmeans	Plot Method for 'tclust' and 'tkmeans' Objects
print.ctlcurves	Classification Trimmed Likelihood Curves
print.DiscrFact	Discriminant Factor analysis for 'tclust' objects
print.tclust	TCLUST method for robust clustering
print.tclustIC	Performs cluster analysis by calling 'tclust' for different number of groups 'k' and restriction factors 'c'
print.tkmeans	TKMEANS method for robust K-means clustering
randIndex	Calculates Rand type Indices to compare two partitions
rlg	Robust Linear Grouping
simula.rlg	Simulate contaminated data set for applying rlg
simula.tclust	Simulate contaminated data set for applying TCLUST
summary.DiscrFact	The 'summary' method for objects of class 'DiscrFact'
swissbank	Swiss banknotes data
tclust	TCLUST method for robust clustering
tclustIC	Performs cluster analysis by calling 'tclust' for different number of groups 'k' and restriction factors 'c'
tkmeans	TKMEANS method for robust K-means clustering
wholesale	Wholesale customers dataset