Tilted-CCA Factorization — tiltedCCA • tiltedCCA

Computing the common-distinct decomposition via CCA, by setting each latent dimension to the same common tilt.

Usage

tiltedCCA(
  input_obj,
  discretization_gridsize = 21,
  enforce_boundary = F,
  fix_tilt_perc = F,
  verbose = 0
)

Arguments

input_obj

multiSVD class, after creation via compute_snns()

discretization_gridsize

positive integer for how many values between 0 and 1 (inclusive) to search the appropriate amount of tilt over

enforce_boundary

boolean, on whether or not the tilt is required to stay between the two canonical score vectors

fix_tilt_perc

boolean or a numeric. If FALSE, then the tilt is adaptively determined, and if TRUE, then the tilt is set to be equal to 0.5. If numeric, the value should be between 0 and 1, which the tilt will be set to.

verbose

non-negative integer

For the tilt values (possibly set in fix_tilt_perc), values close to 0 or 1 means the common space resembles the canonical scores of mat_2 or mat_1 respectively.

Value

updated multiSVD object