plot.fastPLS: Plot PLS latent scores

In fastPLS: Fast Partial Least Squares for High-Dimensional Data

Plot PLS latent scores

Description

Draws a two-component score plot for a fitted fastPLS object. Optional ellipses are computed either as data confidence ellipses or Hotelling T2 score ellipses. Axis labels include predictor-space variance explained when it was requested during model fitting.

Usage

## S3 method for class 'fastPLS'
plot(
  x,
  comps = c(1L, 2L),
  groups = NULL,
  score.set = c("auto", "train", "test"),
  ellipse = FALSE,
  ellipse.type = c("confidence", "hotelling"),
  conf = 0.95,
  ...
)

Arguments

x	A fitted fastPLS object.
comps	Two component indices.
groups	Optional grouping vector used for point fills and grouped ellipses.
score.set	Plot train scores, test scores, or use auto to select stored training scores before test scores.
ellipse	Draw confidence ellipses when TRUE.
ellipse.type	Use confidence or hotelling ellipses.
conf	Confidence level.
...	Additional arguments passed to plot().

Value

Invisibly returns the plotted score matrix.

Examples

X <- as.matrix(iris[, seq_len(4)])
fit <- pls(X, iris$Species,
    ncomp = 2, fit = TRUE,
    return_variance = TRUE, seed = 1
)
plot(fit, groups = iris$Species, ellipse = TRUE)

fastPLS documentation built on Sept. 29, 2026, 1:06 a.m.