Hi all,
Is there any package in Julia to compute distance correlation just like the package energy in r?
Thank you,
Perhaps this is what you are searching for:
https://github.com/JuliaStats/Distances.jl
CorrDist corr_dist(x, y) cosine_dist(x - mean(x), y - mean(y))
2 Likes
I don’t think the two functions are calculating the same thing.
julia> using RCall
julia> x = randn(10);
julia> y = randn(10);
julia> R"library(energy)"; rcall(:dcor, x, y)
RObject{RealSxp}
[1] 0.4823483
julia> using Distances
julia> corr_dist(x, y)
0.8597077631762767
I think it is quite easy in julia to implement a simplified (and also more performant) version for distance correlation from scratch. If it is not in a performance critical part, you can also use RCall.jl to use functions from R.
1 Like
No, they are not! In fact, this small example shows that the version of cordist implemented in distances.jl is not always between 0 and 1 unlike the definition in here. Also it seems higher distances are associated with stronger independence - opposite to dcor.
n=50
p = 3
q = 5
Y = randn(n, q)
X = randn(n, p)
Y[:,1] = X[:,1]
pairwise(CorrDist(), Y, X, dims=2)
Currently, I am using RCall (dcor in r) to compute the distance correlation. This is too expensive in an MC simulation. I have not been able to implement a better and fast version.
Yes! That works better. Exactly what I was looking for.
Many thanks!