| 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 |