T1: Interactive Tucker1 analysis
In ThreeWay: Three-Way Component Analysis

Description Usage Arguments Value Author(s) References See Also Examples

Detects the underlying structure of a three-way array according to the Tucker1 (T1) model.

1 2	T1(dati, laba, labb, labc)

`dati`	Array of order `n` by `m` by `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

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
`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`)
`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

Maria Antonietta Del Ferraro mariaantonietta.delferraro@yahoo.it
Henk A.L. Kiers h.a.l.kiers@rug.nl
Paolo Giordani paolo.giordani@uniroma1.it

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.

CP,T3,T2

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 T1 analysis
BusT1 <- T1(Bus, laba, labb, labc)
# interactive T1 analysis (when labels are not available)
BusT1 <- T1(Bus)

## End(Not run)