nipals.fit: NIPALS PLS with missing values

In pls: Partial Least Squares and Principal Component Regression

NIPALS PLS with missing values

Description

A NIPALS implementation that tolerates NAs in both X and Y by ignoring them when updating scores and loadings. This is useful when the design matrix is incomplete but the number of components is relatively low.

Usage

nipals.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.
ncomp	number of PLS components to extract.
center	logical whether to center X and Y before fitting. Means ignore missing entries.
stripped	logical. If TRUE only the coefficients and the mean vectors are returned.
maxiter	maximum number of inner iterations to force convergence on each component.
tol	tolerance used to stop the inner loop when the direction vector changes very little.
...	currently ignored.

Value

A list with the same components as nipals.fit, but the computations never fail in the presence of missing entries.

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