Resigns Multi-Way Factors
Resigns factors from a multiway object.
## S3 method for class 'cpd' resign(x, mode = 1, newsign = 1, absorb = 3, ...) ## S3 method for class 'indscal' resign(x, mode = "B", newsign = 1, ...) ## S3 method for class 'mcr' resign(x, mode = "A", newsign = 1, absorb = "C", ...) ## S3 method for class 'parafac' resign(x, mode = "A", newsign = 1, absorb = "C", ...) ## S3 method for class 'parafac2' resign(x, mode = "A", newsign = 1, absorb = "C", method = "pearson", ...) ## S3 method for class 'sca' resign(x, mode = "B", newsign = 1, ...) ## S3 method for class 'tucker' resign(x, mode = "A",newsign = 1, ...)
x |
Object of class "cpd" (output from |
mode |
Character indicating which mode to resign. For "cpd" objects, should be an integer between 1 and N. |
newsign |
Desired resigning for each column of specified mode. Can input a scalar or a vector with length equal to the number of factors for the given mode. If |
absorb |
Character indicating which mode should absorb the inverse of the rescalings applied to |
method |
Correlation method to use if |
... |
Ignored. |
If x is of class "parafac2" and mode="A", the input newsign can be a list where each element contains a covariate vector for resigning Mode A. You need length(newsign[[k]]) = nrow(x$A[[k]]) for all k when newsign is a list. In this case, the resigning is implemented according to the sign of cor(newsign[[k]], x$A[[k]][,1], method). See Helwig (2013) for details.
Same as input.
Nathaniel E. Helwig <helwig@umn.edu>
Helwig, N. E. (2013). The special sign indeterminacy of the direct-fitting Parafac2 model: Some implications, cautions, and recommendations, for Simultaneous Component Analysis. Psychometrika, 78, 725-739.
# See examples for... # cpd (Canonical Polyadic Decomposition) # indscal (INividual Differences SCALing) # mcr (Multiway Covariates Regression) # parafac (Parallel Factor Analysis-1) # parafac2 (Parallel Factor Analysis-2) # sca (Simultaneous Component Analysis) # tucker (Tucker Factor Analysis)
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