Description Usage Arguments Value Note Author(s) References See Also Examples
Computes PCASup analysis for the directions concerning the reduced modes.
1 | pcasup2(X, n, m, p, model)
|
X |
Matrix (or data.frame coerced to a matrix) of order ( |
n |
Number of |
m |
Number of |
p |
Number of |
model |
Tucker2 model choice (1 for T2-AB, 2 for T2-AC, 3 for T2-BC) |
A list including the following components:
A |
Matrix of the eingenvectors of the supermatrix containing the frontal slices of the array ( |
B |
Matrix of the eingenvectors of the supermatrix containing the horizontal slices of the array ( |
C |
Matrix of the eingenvectors of the supermatrix containing the lateral slices of the array ( |
la |
Vector of the eigenvalues of the supermatrix containing the frontal slices of the array ( |
lb |
Vector of the eigenvalues of the supermatrix containing the horizontal slices of the array ( |
lc |
Vector of the eigenvalues of the supermatrix containing the lateral slices of the array ( |
Cumulative sum of eigenvalues and fits from PCAsup applied to the reduced modes are automatically printed.
Maria Antonietta Del Ferraro mariaantonietta.delferraro@yahoo.it
Henk A.L. Kiers h.a.l.kiers@rug.nl
Paolo Giordani paolo.giordani@uniroma1.it
H.A.L. Kiers (1991). Hierarchical relations among three-way methods. Psychometrika 56: 449–470.
H.A.L. Kiers (2000). Towards a standardized notation and terminology in multiway analysis. Journal of Chemometrics 14:105–122.
L.R Tucker (1966). Some mathematical notes on three-mode factor analysis. Psychometrika 31: 279–311.
1 2 3 |
PCASUP: eigenvalues mode A
Eigenvalue Fit(%)
Comp.1 394418.41 98.04
Comp.2 4973.00 99.28
Comp.3 1300.18 99.60
Comp.4 648.39 99.76
Comp.5 400.69 99.86
Comp.6 318.45 99.94
Comp.7 242.88 100.00
PCASUP: eigenvalues mode B
Eigenvalue Fit(%)
Comp.1 396973.69 98.68
Comp.2 3403.74 99.52
Comp.3 1251.26 99.83
Comp.4 377.82 99.93
Comp.5 295.50 100.00
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.