fsdaR (version 0.4-9)

tclusteda.object: Objects returned by the function tclustfsda with the option monitoring=TRUE

Description

An object of class tclusteda.object holds information about the result of a call to tclustfsda with the option monitoring=TRUE.

Value

The functions print() and summary() are used to obtain and print a summary of the results. An object of class tclusteda is a list containing at least the following components:

call

the matched call

k

number of groups

alpha

trimming level

restrfactor

restriction factor

IDX

an n-by-length(alpha) vector containing assignment of each unit to each of the k groups. Cluster names are integer numbers from 1 to k. 0 indicates trimmed observations. The first column refers to alpha[1], the second column refers to alpha[2], ..., the last column refers to alpha[length(alpha)].

MU

a 3 dimensional array of size k-by-p-by-length(alpha) containing the monitoring of the centroid for each value of alpha. MU[,,1], refers to alpha[1] ..., MU(,,length(alpha)] refers to alpha[length(alpha)]. The first row in each slice refers to group 1, second row refers to group 2, etc.

SIGMA

A list of length length(alpha) containing in element j, with j=1, 2, ..., length(alpha), the 3D array of size p-by-p-by-k containing the k (constrained) estimated covariance matrices associated with alpha[j].

Amon

Amon stands for alpha monitoring. Matrix of size (length(alpha)-1)-by-4 which contains for two consecutive values of alpha the monitoring of three quantities (change in classification, change in centroid location, change in covariance location).

• 1st col = value of alpha.

• 2nd col = ARI index.

• 3rd col = squared Euclidean distance between centroids.

• 4th col = squared Euclidean distance between covariance matrices.

Examples

# NOT RUN {
 
# }
# NOT RUN {
 data(hbk)
 (out <- tclustfsda(hbk[, 1:3], k=2, monitoring=TRUE))
 class(out)
 summary(out)
 
# }