The alr-transform maps a composition in the D-part Aitchison-simplex
non-isometrically to a D-1 dimensonal euclidian vector, treating the
last part as common denominator of the others. The data can then
be analysed in this transformation by all classical multivariate
analysis tools not relying on a distance. The interpretation of
the results is relatively simple, since the relation to the original D-1
first parts is preserved. However distance is an extremely relevant
concept in most types of analysis, where a clr or
ilr transformation should be preferred.
The additive logratio transform is given by
$$ alr(x)_i := \ln\frac{x_i}{x_D} $$.
References
Aitchison, J. (1986) The Statistical Analysis of Compositional
Data Monographs on Statistics and Applied Probability. Chapman &
Hall Ltd., London (UK). 416p.