Description Usage Arguments References Examples
This is an implementation of the T3Clusf algorithm of Rocci & Vichi (2005).
1 2 3  T3Clusf(X, Q, R = Q, G = 2, margin = 3L, alpha = 1, eps = 1e08,
maxit = 100L, verbose = 1, nstart = 1L, parallel = TRUE,
mc.cores = detectCores()  1L, minsize = 3L)

X 
Threeway data array, with no missing values. 
Q 
Integer giving the number of dimensions required for mode B (variables).
This is the first mode of the array, excluding the mode clustered over (see 
R 
Integer giving the number of dimensions required for mode C (occasions).
This is the second mode of the array, excluding the mode clustered over (see 
G 
Integer giving the number of clusters required. 
margin 
Integer giving the margin of the array to cluster over. The remaining two
modes, in the original order, corresponds to 
alpha 
Numeric value giving the fuzziness parameter. 
eps 
Small numeric value giving the empirical convergence threshold. 
maxit 
Integer giving the maximum number of iterations allowed. 
verbose 
Integer giving the number of iterations after which the loss values are printed. 
nstart 
Integer giving the number of random starts required. 
parallel 
Logical indicating whether to parallelize over random starts if

mc.cores 
Argument passed to 
minsize 
Integer giving the minimum size of cluster to uphold when reinitializing empty clusters. 
Rocci, R., & Vichi, M. (2005). Threemode component analysis with crisp or fuzzy partition of units. Psychometrika, 70(4), 715736.
1 2 3 
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.