Computes all the approximated Tucker2 solutions using PCASup results with r1 (from 1 to maxa, if A-mode reduced), r2 (from 1 to maxb, if B-mode reduced) and r3 (from 1 to maxc, if C-mode reduced) components.
Usage
T2runsApproxFit(X, n, m, p, maxa, maxb, maxc, model)
Arguments
X
Matrix (or data.frame coerced to a matrix) of order (nxmp) containing the matricized array (frontal slices)
n
Number of A-mode entities
m
Number of B-mode entities
p
Number of C-mode entities
maxa
Maximum dimensionality for the A-mode
maxb
Maximum dimensionality for the B-mode
maxc
Maximum dimensionality for the C-mode
model
Tucker2 model choice (1 for T2-AB, 2 for T2-AC, 3 for T2-BC)
Value
out
Matrix with columns: number of components for the A-mode, number of components for the B-mode, number of components for the C-mode, goodness of fit (%), total number of components
References
H.A.L. Kiers (1991). Hierarchical relations among three-way methods. Psychometrika 56:449--470.
data(Bus)
# Fit values of T2-AB with different numbers of components # (from 1 to 3 for the B-mode, from 1 to 5 for the C-mode)FitT2 <- T2runsApproxFit(Bus, 7, 5, 37, 7, 3, 5, 3)