heterogeneous populations is a problem encountered in
applied fields such as Bioinformatics.
We propose priors based on spectral decompostions for these problems
inspired from both Random matrix theory and simulations.
This allows us to address questions on eventual underlying categorical
variables as well as hidden gradients.