Closed 1danjordan closed 3 years ago
👀👀👀 !!
On Sun, Apr 5, 2020, 5:50 PM Daniel Jordan notifications@github.com wrote:
Distributions.jl uses a reference file to verify correctness of their implementation. Surprisingly, they also have a practically complete R package https://github.com/JuliaStats/Distributions.jl/blob/master/test/ref/discrete_test.ref.json in R6 they used to create this reference file. See the reference files for discrete distributions https://github.com/JuliaStats/Distributions.jl/blob/master/test/ref/discrete_test.ref.json and continuous distributions https://github.com/JuliaStats/Distributions.jl/blob/master/test/ref/continuous_test.ref.json .
We could leverage their reference file to use in verifying distributions3, in a similar manner to how they do so. This would require a bit of code to map each distribution in distributions3 to the entry in each JSON file. I think this would be more robust and (once written) accelerate development/introduction of new distributions because the test would essentially already be written!
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I think simplest solution is to just copy the files over and rename the distributions to match the names of our distributions. It won't be reproducible, but can clearly document. The reference files haven't been updated for 3 years, so I don't think it's worth the time to ensure full reproducibility right now.
Being locked at home, I've found the time to work on distributions3
some more. Will start working on a PR.
Closing this unless something wants to actively work on it.
Distributions.jl uses a reference file to verify correctness of their implementation. Surprisingly, they also have a practically complete R package in R6 they used to create this reference file. See the reference files for discrete distributions and continuous distributions.
We could leverage their reference file to use in verifying
distributions3
, in a similar manner to how they do so. This would require a bit of code to map each distribution indistributions3
to the entry in each JSON file. I think this would be more robust and (once written) accelerate development/introduction of new distributions because the test would essentially already be written!