Hi all,

Is there any package in Julia to compute distance correlation just like the package energy in r?

Thank you,

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:

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!