calls microaggregation code from mu-argus. In case only one variable should be
microaggregated and `useOptimal`

is `TRUE`

, Hansen-Mukherjee polynomial exact method
is applied. In any other case, the Mateo-Domingo method is used.

`argus_microaggregation(df, k, useOptimal = FALSE)`

- df
a

`data.frame`

with only numerical columns- k
required group size

- useOptimal
(logical) should optimal microaggregation be applied (ony possible in in case of one variable)

a `list`

with two elements

original: the originally provided input data

microaggregated: the microaggregated data.frame

mu-Argus manual at https://github.com/sdcTools/manuals/raw/master/mu-argus/MUmanual5.1.pdf

```
mat <- matrix(sample(1:100, 50, replace=TRUE), nrow=10, ncol=5)
df <- as.data.frame(mat)
res <- argus_microaggregation(df, k=5, useOptimal=FALSE)
```