plo_sup: Plot of Supplementary Variables

In morepls: Interpretation Tools for Partial Least Squares Regression

Plot of Supplementary Variables

Description

Plots the categories of supplementary variables for a PLS regression.

Usage

plo_sup(object, vars, excl = NULL, comps = c(1,2),
 shapesize = 2, textsize = 3, vlab = TRUE, force = 1,
 max.overlaps = Inf, dashes = TRUE)

Arguments

object	an object of class mvr from pls package
vars	A data frame of categorical supplementary variables. All these variables should be factors.
excl	character vector of supplementary categories to exclude from the plot, specified in the form "namevariable.namecategory" (for instance "Gender.Men"). If NULL (default), all the supplementary categories are plotted.
comps	the components to use. Default is c(1,2).
shapesize	Size of the shapes. Default is 2.
textsize	Size of the labels of categories. Default is 3.
vlab	Logical. If TRUE (default), the variable name is added as a prefix for the labels of the categories.
force	Force of repulsion between overlapping text labels. Defaults to 1. If 0, labels are not repelled at all.
max.overlaps	Exclude text labels that overlap too many things. Defaults to Inf, which means no labels are excluded.
dashes	Logical. Should one add lines between categories ? Default is TRUE.

Value

a ggplot2 object

Author(s)

Nicolas Robette

References

Martens, H., Næs, T. (1989) Multivariate calibration. Chichester: Wiley.

Tenenhaus, M. (1998) La Regression PLS. Theorie et Pratique. Editions TECHNIP, Paris.

See Also

plo_var

Examples

library(pls)
data(mpg, package = "ggplot2")
pls <- mvr(displ ~ cty + hwy + cyl,
           ncomp = 3,
           data = mpg,
           validation = "CV",
           method = "oscorespls")
supvars <- data.frame(class = factor(mpg$class), trans = factor(mpg$trans))
plo_sup(pls, supvars, dashes = FALSE)

morepls documentation built on June 8, 2025, 10:34 a.m.