dot-compute_unnormalized_scores: Using the CCA solution, compute the score matrices.
In linnykos/multiomicCCA: Tilted CCA
.compute_unnormalized_scores R Documentation
Using the CCA solution, compute the score matrices.
Description
This is called by .tiltedCCA_common_score. It's called unnormalized
scores since if there are n rows (i.e., nrow(svd_1$u)),
then the return matrices will be orthogonal matrices where the
matrix multiplied by itself is a diagonal matrix with all values n.
Usage
.compute_unnormalized_scores(svd_1, svd_2, cca_res)
Arguments
svd_1
SVD of the denoised variant of mat_1 from dcca_factor
svd_2
SVD of the denoised variant of mat_2 from dcca_factor
cca_res
returned object from .cca
Value
list of two matrices
linnykos/multiomicCCA documentation built on July 17, 2025, 3:16 a.m.
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| .compute_unnormalized_scores | R Documentation |
Using the CCA solution, compute the score matrices.
Description
This is called by .tiltedCCA_common_score. It's called unnormalized
scores since if there are n rows (i.e., nrow(svd_1$u)),
then the return matrices will be orthogonal matrices where the
matrix multiplied by itself is a diagonal matrix with all values n.
Usage
.compute_unnormalized_scores(svd_1, svd_2, cca_res)
Arguments
svd_1 |
SVD of the denoised variant of |
svd_2 |
SVD of the denoised variant of |
cca_res |
returned object from |
Value
list of two matrices
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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