In the documentation for RooNDKeysPdf it is stated, that the multi-dimensional kernel-estimation ensures “The kernels are constructed such that they reflect the correlation coefficients between the observables in the input dataset.” but I can’t seem to find any further documentation for this. In the note: cds.cern.ch/record/477613 documenting the underlying algorithms the problem is mentioned but, perhaps due to lack of understanding, I cannot see how this is done still.
I’m currently using RooNDKeysPdf to model distributions for a Mutual Information measure of non-linear correlation in ATLAS data and need to know how the correlations are handled for this. Any help to my ignorance or to the lack of documentation will be most appreciated!
/Ask