DiscrFact {tclust}

Discriminant Factor analysis for tclust objects

Description

Analyzes 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).

Usage

DiscrFact(x, threshold = 1/10)

Arguments

x

A tclust object.

threshold

A cluster assignment or a trimming decision for an observation with a discriminant factor larger than log(threshold) is considered a "doubtful" decision.

Value

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).

References

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>