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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

Run this code
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)

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