Copulas.jl
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lrnv
A fully `Distributions.jl`-compliant copula package
I think this is an upstream problem - the `copula` (and hence also `input_distribution`) lost the type information and generate samples of type `Float64`. _Originally posted by @devmotion in https://github.com/SciML/GlobalSensitivity.jl/pull/158#discussion_r1550752719_
We could use something like that to proof-read the docs again : https://forem.julialang.org/danielvandh/efficiently-fixing-typos-in-documentation-1j88
See there : https://jds-online.org/journal/JDS/article/1266/info to be able to fit student copula.
Some of the models are still lacking estimation procedures at all. All models that have a density should be able to provide a MLE estimation procedure to perform IFM via...
It would be nice to propose vines copulas. Step One would be to find a right source to devise the code structure necessary to iplement such models. Step Two would...
The following properties of the copulas: - kendall tau - spearman rho - tail dependence coefficients should be clarified and included into the general API. it is weird that we...
As noted by @lidiamandre in #50 , implementing the option to use extreme values copulas would be neat :) We may take a look at the R evd package to...
```julia function Distributions.fit(D::SklarDist, x) # The first thing to do is to fit the marginals : @assert length(D) == size(x, 1) # One could put fit but EM works for...
Is there some benchmark? I wonder how much speed improvement when it's compared with `copulapdf` function in Matlab.
So that W and M are in the same parametric family, ref https://github.com/AnderGray/ProbabilityBoundsAnalysis.jl/issues/42