nipalspc.fit: NIPALS PCR with missing values

In pls: Partial Least Squares and Principal Component Regression

NIPALS PCR with missing values

Description

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.

Usage

nipalspc.fit(
  X,
  Y,
  ncomp,
  center = TRUE,
  stripped = FALSE,
  maxiter = 500,
  tol = 1e-06,
  ...
)

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 TRUE both X and Y are centered column-wise (ignoring missing entries).
stripped	logical. When TRUE only 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.

Value

A list mirroring the return value of svdpc.fit but computed via the NA-robust NIPALS PCR updates.

pls documentation built on Feb. 21, 2026, 9:07 a.m.