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Uncertainty handling

All high-level causality test are integrated with the uncertainty handling machinery in UncertainData.jl. Any combination of real-valued vectors, Vector{<:AbstractUncertainValue}, or AbstractUncertainValueDataset are accepted as inputs to causality, making uncertainty quantification on the causality statistics a breeze.

For more fine grained control over the analysis, check out the syntax overview for low-level estimators.

List of causality methods for uncertain data

If both indices and values have uncertainties, use one of the following methods:

• Naive resampling
• Naive constrained resampling
• Binned resampling
• Strictly increasing, interpolated resampling
• Interpolate-and-bin resampling