Run sparse SVD — run_sparsesvd • phenomix

Run sparse Singular Value Decomposition (sparseSVD).

run_sparsesvd(
  mat,
  transpose = TRUE,
  add_names = TRUE,
  rank = 0L,
  tol = 1e-15,
  kappa = 1e-06
)

Arguments

mat	Matrix to run sparseSVD on.
transpose	Whether to transpose the matrix first.
add_names	Add colnames and rownames to embeddings and loadings.
rank	an integer specifying the desired number of singular components, i.e. the rank of the truncated SVD. Specify 0 to return all singular values of magnitude larger than `tol` (default).
tol	exclude singular values whose magnitude is smaller than `tol`
kappa	accuracy parameter \(\kappa\) of the SVD algorithm (with SVDLIBC default)