Performs the identical models known as PARAFAC or CANDECOMP model.
CANDPARA(X,dim=3,test=1E-8,Maxiter=1000,
smoothing=FALSE,smoo=list(NA),
verbose=getOption("verbose"),file=NULL,
modesnam=NULL,addedcomment="")a CANDPARA (inherits from PTAk) object
a tensor (as an array) of order k, if non-identity metrics are
used X is a list with data as the array and
met a list of metrics.
a number specifying the number of rank-one tensors
control of convergence
maximum number of iterations allowed for convergence
see SVDgen
see PTA3
control printing
output printed at the prompt if NULL, or printed in the given file
character vector of the names of the modes, if NULL
"mo 1" ..."mo k"
character string printed after the title of the analysis
Didier G. Leibovici
Looking for the best rank-one tensor approximation (LS) the three methods described in the package are equivalent. If the number of tensors looked for is greater then one the methods differs: PTA-kmodes will look for best approximation according to the orthogonal rank (i.e. the rank-one tensors are orthogonal), PCA-kmodes will look for best approximation according to the space ranks (i.e. the ranks of all (simple) bilinear forms , that is the number of components in each space), PARAFAC/CANDECOMP will look for best approximation according to the rank (i.e. the rank-one tensors are not necessarily orthogonal). For sake of comparisons the PARAFAC/CANDECOMP method and the PCA-nmodes are also in the package but complete functionnality of the use these methods and more complete packages may be checked at the www site quoted below.
Caroll J.D and Chang J.J (1970) Analysis of individual differences in multidimensional scaling via n-way generalization of 'Eckart-Young' decomposition. Psychometrika 35,283-319.
Harshman R.A (1970) Foundations of the PARAFAC procedure: models and conditions for 'an explanatory' multi-mode factor analysis. UCLA Working Papers in Phonetics, 16,1-84.
Kroonenberg P (1983) Three-mode Principal Component Analysis: Theory and Applications. DSWO press. Leiden.)
Leibovici D and Sabatier R (1998) A Singular Value Decomposition of a k-ways array for a Principal Component Analysis of multi-way data, the PTA-k. Linear Algebra and its Applications, 269:307-329.