This function is mainly aimed to investigate heterogeneous relative variation
structures in compositional data sets containing zeros or unobserved values. For each pattern of zero or unobserved values,
log-ratio variances (upper triangle of variation matrix) and means (lower triangle of variation matrix) are computed from the
available data. Note that (1) NAs are produced for log-ratio variances and means in groups containing less than two observations,
and (2) at least two components must be available in each group to compute log-ratios.
The overall estimate is obtained across groups by pairwise deletion. Note that, unlike the ordinary var
function, maximum likelihood estimates of the variances are computed. That is,
the observed sum of squares is divided by the corresponding number of observations n and not by n-1.
Group-wise variation arrays can be obtained from fully observed zero-free data by setting a grouping factor
using the argument groups
.