Compute the uncentered log ratio transform of a (dataset of)
composition(s) and its inverse.
Usage
ult( x ,...)
ultInv( z ,..., orig=gsi.orig(z))
Kappa( x ,...)
Value
ult gives the uncentered log transform,
ultInv gives closed compositions with the given
ult/clr-transforms
Kappa gives the difference between the clr and the ult
transforms. It is quite linked to information measures.
Arguments
x
a composition or a data matrix of compositions, not necessarily closed
z
the ult-transform of a composition or
clr-transforms of compositions (or a data matrix), not necessarily centered
...
for generic use only
orig
a compositional object which should be mimicked
by the inverse transformation. It is the generic
argument. Typically the orig argument is stored as an attribute
in z and will be extracted automatically by this function; if this
fails, orig can be set equal to the dataset that
was transformed in the first place.
The ult-transform is simply the elementwise log of the closed
composition. The ult has some important properties in the scope
of Information Theory of probability vectors (but might be mostly
misleading for exploratory analysis of compositions). DO NOT USE if
you do not know what you are doing.