Give UnivariateKDE distribution-like overloads

JuliaStats / KernelDensity.jl

Kernel density estimators for Julia

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Give UnivariateKDE distribution-like overloads #91

Open ChrisRackauckas opened 3 years ago

ChrisRackauckas commented 3 years ago

Upstreams https://github.com/SciML/DiffEqUncertainty.jl/pull/41 . Allows for it to be "distribution-like". Still missing the random sampling.

agerlach commented 3 years ago

Any status update on getting this PR merged?

tpapp commented 3 years ago

Is it actually guaranteed that the the support is zero outside the extrema of x? I would have to look at the code, but I don't think it holds in general. Eg for a Normal kernel (which is the default), the support is the real line. x are just the points where it is precalculated.