I was wondering if there is a method to get a conditional distribution out of a multivariate kde in julia, preferably using the package KernelDensityEstimate.jl.
So say for example that I have the following code:
using KernelDensityEstimate, Distributions # define number of samples const n_samples = 500 # define two correlated variables const x = randn(n_samples) const y = x.^2 .+ rand(Uniform(-0.0005, 0.0005), n_samples) # and an uncorrelated one const z = rand(Gamma(), n_samples); # fit the kde kde = kde!(Array((hcat(x,y,z)')))
And I would like to get the distribution of x and y conditioned to, say, z = 10.0.
It would be ok for me if the solution uses a multivariate KDEs package different from KernelDensityEstimate.jl, as long as it implements a
Thank you very much