# Robust Trimmed Clustering

## Documentation for package ‘tclust’ version 2.1-0

- 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