pcaCoDa {robCompositions} | R Documentation |
This function performs out a robust principal component analysis for compositional data.
pcaCoDa(x, method = "robust")
x |
compositional data |
method |
either “robust” (default) or ‘standard’ |
The compositional data set is transformed using the ilr tranformation. Afterwards, robust principal component analysis is performed. Resulting loadings and scores are back-transformed to the clr space where the compositional biplot can be shown.
scores |
scores in clr space |
loadings |
loadings in clr space |
eigenvalues |
eigenvalues of the clr covariance matrix |
method |
method |
princompOutputClr |
output of princomp needed in plot.pcaCoDa |
K. Hron, P. Filzmoser, M. Templ
Filzmoser, P., Hron, K., Reimann, C. (2009) Principal Component Analysis for Compositional Data with Outliers. Environmetrics, accepted for publication.
data(aitchison395) p1 <- pcaCoDa(aitchison395) p1 plot(p1)