rescale {multiway}

Rescales Multi-Way Factors

Description

Rescales factors from a multiway object.

Usage

## S3 method for class 'cpd'
rescale(x, mode = 1, newscale = 1, absorb = 3, ...)
## S3 method for class 'indscal'
rescale(x, mode = "B", newscale = 1, ...)
## S3 method for class 'mcr'
rescale(x, mode = "A", newscale = 1, absorb = "C", ...)
## S3 method for class 'parafac'
rescale(x, mode = "A", newscale = 1, absorb = "C", ...)
## S3 method for class 'parafac2'
rescale(x, mode = "A", newscale = 1, absorb = "C", ...)
## S3 method for class 'sca'
rescale(x, mode = "B", newscale = 1, ...)
## S3 method for class 'tucker'
rescale(x, mode = "A", newscale = 1, ...)

Arguments

x

Object of class "indscal" (output from indscal), class "mcr" (output from mcr), class "parafac" (output from parafac), class "parafac2" (output from parafac2), class "sca" (output from sca), or class "tucker" (output from tucker).

mode

Character indicating which mode to rescale. For "cpd" objects, should be an integer between 1 and N.

newscale

Desired root mean-square for each column of rescaled mode. Can input a scalar or a vector with length equal to the number of factors for the given mode.

absorb

Character indicating which mode should absorb the inverse of the rescalings applied to mode (cannot be equal to mode). For "cpd" objects, should be an integer between 1 and N.

...

Ignored.

Details

See cpd, indscal, mcr, parafac, parafac2, sca, and tucker for more details.

Value

Same as input.

Author(s)

Nathaniel E. Helwig <[e-mail]>

References

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.

Examples

# 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)