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
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