I'm working on Bayesian Network and I need to find a broad range of statistical test for testing independence and conditional independence between 2 variables with a potential conditioning set of important size.
My data is a mix of normal (not the most common), non normal (the most common), continuous (the most common), discrete, with dependences being not linear.
So far I was using Z-fisher test as I found a nice implementation in the
bnt toolbox for MATLAB (I'm not so good in developing) but it assumes linearity and normality which are really heavy assumptions.
I found two or three implementation of the Hilbert Schmidt Independence Criteria but, unfortunately, they perform quite poorly.
Do you have some advice? Pointers?
I would like to design a kind of super class of test which will have access to a specific test depending on the nature of the parameters (testing continuous independent of discrete conditional on a continuous variable is still a bit unclear for me).