biplot.pcaCoDa: Biplot method

In robCompositions: Compositional Data Analysis

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

pcaCoDa, plot.pcaCoDa

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)

robCompositions documentation built on Aug. 25, 2023, 5:13 p.m.