The plot method for class ctlcurves: This function plots a ctlcurves object, comparing the target functions values with different values of parameter restr.fact.
The plot method for class DiscrFact: Next to a plot of the tclust object which has been used for creating the DiscrFact object, a silhouette plot indicates the presence of groups with a large amount of doubtfully assigned observations. A third plot similar to the standard tclust plot serves to highlight the identified doubtful observations.
geyser2
(Package: tclust) :
Old Faithful Geyser Data
A bivariate data set obtained from the Old Faithful Geyser, containing the eruption length and the length of the previous eruption for 271 eruptions of this geyser in minutes.
discr_coords
(Package: tclust) :
Discriminant coordinates/canonical variates of tclust objects
Computes the two first discriminant coordinates (canonical coordinates) directly from a tclust object to obtain a graphical representations of cluster solutions in higher dimensional (p > 2) cases.
The function applies tclust several times on a given dataset while parameters alpha and k are altered. The resulting object gives an idea of the optimal trimming level and number of clusters considering a particular dataset.
DiscrFact
(Package: tclust) :
Discriminant Factor Analysis for tclust Objects
Analyzes a tclust-object by calculating discriminant factors and comparing the quality of the actual cluster assignments and the second best possible assignment for each observation. Discriminant factors, measuring the strength of the "trimming" decision may also be defined. Cluster assignments of observations with large discriminant factors are considered as "doubtful" decisions. Silhouette plots give a graphical overview of the discriminant factors distribution (see plot.DiscrFact). More details can be found in GarcÃa-Escudero et al. (2010).
tclust
(Package: tclust) :
General Trimming Approach to Robust Cluster Analysis
tclust searches for k (or less) clusters with different covariance structures in a data matrix x. Relative cluster scatter can be restricted by a constant value restr.fact. For robustifying the estimation, a proportion alpha of observations may be trimmed. In particular, the trimmed k-means method (tkmeans)is represented by the tclust method, setting parameters restr = "eigen", restr.fact = 1 and equal.weights = TRUE.
providing 
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