The clr-transform maps a composition in the D-part Aitchison-simplex
isometrically to a D-dimensonal euclidian vector subspace: consequently, the
transformation is not injective. Thus resulting covariance matrices
are always singular.
The data can then
be analysed in this transformation by all classical multivariate
analysis tools not relying on a full rank of the covariance. See
ilr and alr for alternatives. The
interpretation of the results is relatively easy since the relation between each original
part and a transformed variable is preserved.
The centered logratio transform is given by
$$ clr(x) := \left(\ln x_i - \frac1D \sum_{j=1}^D \ln x_j\right)_i $$
The image of the clr is a vector with entries
summing to 0. This hyperplane is also called the clr-plane.
References
Aitchison, J. (1986) The Statistical Analysis of Compositional
Data, Monographs on Statistics and Applied Probability. Chapman &
Hall Ltd., London (UK). 416p.