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P. Filzmoser, K. Hron:
"Correlation Analysis for Compositional Data";
Mathematical Geosciences, 41 (2012), 8; S. 905 - 919.

Compositional data need a special treatment prior to correlation analysis. In this paper we argue why standard transformations
for compositional data are not suitable for computing correlations, and why the use of raw or log-transformed data is neither
meaningful. As a solution, a procedure based on balances is outlined, leading to sensible correlation measures. The construction
of the balances is demonstrated using a real data example from geochemistry. It is shown that the considered correlation measures
are invariant with respect to the choice of the binary partitions forming the balances. Robust counterparts to the classical,
non-robust correlation measures are introduced and applied. By using appropriate graphical representations, it is shown how
the resulting correlation coefficients can be interpreted.

http://dx.doi.org/10.1007/s11004-008-9196-y

http://www.researchgate.net/publication/225733375_Correlation_Analysis_for_Compositional_Data