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Visualising PLS Fits with bigPLSR

Frédéric Bertrand

Cedric, Cnam, Paris
frederic.bertrand@lecnam.net

2026-09-30

library(bigPLSR)
set.seed(101)

Example data

n <- 80; p <- 6
X <- matrix(rnorm(n * p), n, p)
Y <- scale(X[, 1:2] %*% matrix(c(0.7, -0.4, 0.5, 0.8), 2, 2) + rnorm(n * 2, sd = 0.15))

groups <- factor(rep(LETTERS[1:4], length.out = n))
fit <- pls_fit(X, Y, ncomp = 3, scores = "r")

Score plots with ellipses

plot_pls_individuals(fit, comps = c(1, 2), groups = groups,
                     ellipse = TRUE, ellipse_level = 0.90, 
                     main="Component scores with 90% ellipses")

Variable correlations and biplots

plot_pls_variables(fit, comps = c(1, 2), main="Variable plot")
plot_pls_biplot(fit, comps = c(1, 2), groups = groups,
                ellipse = TRUE, ellipse_level = 0.90, 
                main="Biplot with grouped individuals")

Bootstrap summaries

boot <- pls_bootstrap(X, Y, ncomp = 2, R = 30, type = "xy",
                      parallel = "none", seed = 99)
summary_boot <- summarise_pls_bootstrap(boot)
summary_boot
plot_pls_bootstrap_coefficients(boot, main="Bootstrap coefficient intervals")
boot <- pls_bootstrap(X, Y, ncomp = 2, R = 30, type = "xy", 
                      parallel = "none", seed = 99, return_scores = TRUE)
plot_pls_bootstrap_scores(boot,main="Bootstrap score dispersion")

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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