Add Julia implementation of LOO-PIT #277
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This reduces load time by 0.5s due to invalidations in Interpolations.
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Even though Interpolations.jl is more widely used for interpolating, I replaced it with DataInterpolations.jl for the smoothing. Interpolations introduces a lot of invalidations (see JuliaMath/Interpolations.jl#514), which is likely the reason why adding it as a dependency increased package load time by 0.5s. DataInterpolation works fine for this application and still supports custom interpolation methods. |
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The reported coverage misses appear to be miscalculations, since each of those cases is tested. |
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This PR adds a Julia implementation of LOO-PIT.
It differs from the Python implementation only in terms of the specific methods defined, preferring positional over keyword arguments. While the Python implementation returns a normal NumPy array, this versions returns a
DimArray, whose dimensions match the observations, unless the data is a scalar.Edit: for discrete data, different interpolation methods from
Interpolations.jlDataInterpolations.jl can be specified.