tclust objectsAnalyzes a tclust-object by calculating discriminant factors
and comparing the quality of the actual cluster assignments to that of the second best
possible assignment for each observation. Cluster assignments of observations
with large discriminant factors are considered "doubtful" decisions. Silhouette
plots give a graphical overview of the discriminant factors distribution
(see plot.DiscrFact). More details can be found in García-Escudero et al. (2011).
DiscrFact(x, threshold = 1/10)The function returns an S3 object of type DiscrFact containing the following components:
x A tclust object.
ylimmin A minimum y-limit calculated for plotting purposes.
ind The actual cluster assignment.
ind2 The second most likely cluster assignment for each observation.
lik The (weighted) likelihood of the actual cluster assignment of each observation.
lik2 The (weighted) likelihood of the second best cluster assignment of each observation.
assignfact The factor log(disc/disc2).
threshold The threshold used for deciding whether assignfact indicates a "doubtful" assignment.
mean.DiscrFact A vector of length k + 1 containing the mean discriminant
factors for each cluster (including the outliers).
A tclust object.
A cluster assignment or a trimming decision for an observation with a
discriminant factor larger than log(threshold) is considered a "doubtful" decision.
García-Escudero, L.A.; Gordaliza, A.; Matrán, C. and Mayo-Iscar, A. (2011), "Exploring the number of groups in robust model-based clustering." Statistics and Computing, 21 pp. 585-599, <doi:10.1007/s11222-010-9194-z>