biplot.sprmda: Biplot for sprmda objects of Sparse PRM discriminant analysis

In sprm: Sparse and Non-Sparse Partial Robust M Regression and Classification

Description

This biplot for sprmda objects visualizes the original variables which contribute to the model and their impact on the latent components as well as the position of the observations in the transformed space. The data is projected onto two of the latent components and colored according to class membership.

Usage

## S3 method for class 'sprmda'
biplot(x, comps = c(1, 2), 
colors = list(scores1="orange", scores2="darkgreen", loadings="red", background="gray84"),
textsize = 6, arrowshapes = c(25, 0.03), labelpos = 0.35, ...)

Arguments

x	object of class sprmda.
comps	vector with two integers, referring to the components to be plotted.
colors	list of four elements named scores1 (for observations of group coded with 1), scores2 (for observations of group coded with -1), loadings and background with color codes or names of colors.
textsize	the text size in which to print the scores and loading names.
arrowshapes	vector of length two containing the angle of the arrowheads and their relative length in npc.
labelpos	numeric value; determines distance of the arrow label to the arrowhead.
...	further arguments. Currently not used.

Details

The sparsity of the biplot is inherited by the sparsity of the model. Only the contributing variables are included in the plot, which can lead to better visualization and easier interpretation.

Author(s)

Irene Hoffmann

References

Hoffmann, I., Filzmoser, P., Serneels, S., Varmuza, K., Sparse and robust PLS for binary classification.

See Also

sprmda

Examples

data(iris)
data <- droplevels(subset(iris,iris$Species!="setosa"))
smod <- sprmda(Species~.,data, a=2, eta=0.7, class="lda")
biplot(smod)

sprm documentation built on May 2, 2019, 9:57 a.m.