The data sets to be analyzed are proportions based on counts. Each row is closed; the proportions total 1.00. I understand the need to transform the raw data to a CoDA simplex, and my reading strongly suggests that the isometric log ratio (ilr) function is the most appropriate for these data.
In Boogaart and Delgado's "Analyzing Compositional Data With R", page 30 describes the various available scaling functions. The advice needed is which is most appropriate for my data sets: 'aplus' -- Aichison (ratio) geometry in the real data space. 'rcomp' -- Real (interval) compositional scale. 'acomp' -- Aichison (ratio) compositional scale. Or, one of the others. Reading several docs leaves me confused over which one should be used for both descriptive statistics and further analyses such as CCA, clustering, or time series. There is no statistics group on stackexchange.com and stackoverflow.com is for programming questions, not statistical questions. If there is a better place for this question, please point me to it as there will be other CoDA questions as the analyses proceed. Rich _______________________________________________ R-sig-ecology mailing list R-sig-ecology@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-ecology
