ThreeWay (version 1.1.3)

T2: Interactive Tucker2 analysis

Description

Detects the underlying structure of a three-way array according to the Tucker2 (T2) model.

Usage

T2(dati, laba, labb, labc)

Arguments

dati

Array of order n x m x p or matrix or data.frame of order (n x mp) containing the matricized array (frontal slices)

laba

Optional vector of length n containing the labels of the A-mode entities

labb

Optional vector of length m containing the labels of the B-mode entities

labc

Optional vector of length p containing the labels of the C-mode entities

Value

A list including the following components:

A

Component matrix for the A-mode

B

Component matrix for the B-mode

C

Component matrix for the C-mode

core

Matricized core array (frontal slices)

fit

Fit value expressed as a percentage

fitValues

Fit values expressed as a percentage upon convergence for all the runs of the CP algorithm (see T2func)

funcValues

Function values upon convergence for all the runs of the CP algorithm (see T2func)

cputime

Computation times for all the runs of the CP algorithm (see T2func)

iter

Numbers of iterations upon convergence for all the runs of the CP algorithm (see T2func)

fitA

Fit contributions for the A-mode entities (see T3fitpartitioning)

fitB

Fit contributions for the B-mode entities (see T3fitpartitioning)

fitC

Fit contributions for the C-mode entities (see T3fitpartitioning)

fitAB

Fit contributions for the A-and mode B component combinations (see T3fitpartitioning)

fitAC

Fit contributions for the A-and mode C component combinations (see T3fitpartitioning)

fitBC

Fit contributions for the B-and mode C component combinations (see T3fitpartitioning)

laba

Vector of length n containing the labels of the A-mode entities

labb

Vector of length m containing the labels of the B-mode entities

labc

Vector of length P containing the labels of the C-mode entities

Xprep

Matrix of order (n x mp) containing the matricized array (frontal slices) after preprocessing used for the analysis

References

P. Giordani, H.A.L. Kiers, M.A. Del Ferraro (2014). Three-way component analysis using the R package ThreeWay. Journal of Statistical Software 57(7):1--23. http://www.jstatsoft.org/v57/i07/. P.M. Kroonenberg (2008). Applied Multiway Data Analysis. Wiley, New Jersey. L.R Tucker (1966). Some mathematical notes on three-mode factor analysis. Psychometrika 31:279--311.

See Also

CP,T3,T1

Examples

data(Bus)
# labels for Bus data
laba <- rownames(Bus)
labb <- substr(colnames(Bus)[1:5], 1, 1)
labc <- substr(colnames(Bus)[seq(1,ncol(Bus),5)], 3, 8)
## Not run: 
# # interactive T2 analysis
# BusT2 <- T2(Bus, laba, labb, labc)
# # interactive T2 analysis (when labels are not available)
# BusT2 <- T2(Bus)
# ## End(Not run)