This performs pca on a sparse Matrix specified by the formula and the tibble.
Arguments
- fo
a formula, like outcome ~ (row_ids & context) * measurement_type.
- tib
a tibble that contains the variables in the formula. The only exception is that the left-hand-side can be 1 and this does not need to be in tib.
- k
number of dimensions for the pca
Value
the output is a list of: (1) row_features for whichever term is first on the right hand side of the formula, (2) column_features for whichever term is second on the right hand side of the formula, (3) middle_B which is a tibble corresponding to a diagonal matrix in sparse triplet form, (4) settings which is a list of details.