A NIPALS-based PCR that tolerates missing entries in both
predictors and responses by only using observed cells when updating scores
and loadings. It follows the same API as svdpc.fit so it can be used
whenever low-level PCR needs to handle incomplete data.
Arguments
- X
numeric matrix (or coercible) of predictors. Missing values are allowed and handled internally.
- Y
numeric matrix (or coercible) of responses. Missing values are also handled internally during the final regression step.
- ncomp
number of PCR components to extract.
- center
logical. If
TRUEbothXandYare centered column-wise (ignoring missing entries).- stripped
logical. When
TRUEonly the coefficients and mean vectors are returned for faster use in resampling.- maxiter
maximum number of inner iterations per component.
- tol
convergence tolerance used when the direction vector stabilizes.
- ...
currently ignored.