| biplot.pcaCoDa {robCompositions} | R Documentation |
Biplot method
Description
Provides robust compositional biplots.
Usage
## S3 method for class 'pcaCoDa'
biplot(x, y, ..., choices = 1:2)
Arguments
x |
object of class ‘pcaCoDa’ |
y |
... |
... |
arguments passed to plot methods |
choices |
selection of two principal components by number. Default: c(1,2) |
Details
The robust compositional biplot according to Aitchison and Greenacre (2002),
computed from (robust) loadings and scores resulting from pcaCoDa, is performed.
Value
The robust compositional biplot.
Author(s)
M. Templ, K. Hron
References
Aitchison, J. and Greenacre, M. (2002). Biplots of compositional data. Applied Statistics, 51, 375-392. \
Filzmoser, P., Hron, K., Reimann, C. (2009) Principal component analysis for compositional data with outliers. Environmetrics, 20 (6), 621–632.
See Also
Examples
data(coffee)
p1 <- pcaCoDa(coffee[,-1])
p1
plot(p1, which = 2, choices = 1:2)
# exemplarly, showing the first and third PC
a <- p1$princompOutputClr
biplot(a, choices = c(1,3))
## with labels for the scores:
data(arcticLake)
rownames(arcticLake) <- paste(sample(letters[1:26], nrow(arcticLake), replace=TRUE),
1:nrow(arcticLake), sep="")
pc <- pcaCoDa(arcticLake, method="classical")
plot(pc, xlabs=rownames(arcticLake), which = 2)
plot(pc, xlabs=rownames(arcticLake), which = 3)
[Package robCompositions version 2.4.1 Index]