pcasup3 {ThreeWay}

PCASup Analysis

Description

Computes PCASup analysis in all the three directions.

Usage

 pcasup3(X, n, m, p)

Arguments

X

Matrix (or data.frame coerced to a matrix) of order (n x mp) containing the matricized array (frontal slices)

n

Number of A-mode entities

m

Number of B-mode entities

p

Number of C-mode entities

Value

A list including the following components:

A

Matrix of the eingenvectors of the supermatrix containing the frontal slices of the array (A-mode)

B

Matrix of the eingenvectors of the supermatrix containing the horizontal slices of the array (B-mode)

C

Matrix of the eingenvectors of the supermatrix containing the lateral slices of the array (C-mode)

la

Vector of the eigenvalues of the supermatrix containing the frontal slices of the array (A-mode)

lb

Vector of the eigenvalues of the supermatrix containing the horizontal slices of the array (B-mode)

lc

Vector of the eigenvalues of the supermatrix containing the lateral slices of the array (C-mode)

Note

pcasup3 computes the Tucker3 solution according to Tucker (1966).
Cumulative sum of eigenvalues and fits from PCAsup applied to the A-, B- and C-modes are automatically printed.

Author(s)

Maria Antonietta Del Ferraro [e-mail]
Henk A.L. Kiers [e-mail]
Paolo Giordani [e-mail]

References

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.

See Also

T3

Examples

data(Bus)
## Not run: 
# PCA-sup
pcasupBus <- pcasup3(Bus, 7, 5, 37)

## End(Not run)