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Tests for econsa's shapley.py and potential improvements

In this repo I write more tests for shapley.py, a method for calculating Shapley effects for quantitative uncertainty analysis.

shapley.py implements the algorithm suggested by Song et al. (2016) which in turn came up with an algorithm based on the idea of using Shapley values for global sensitivity analysis introduced by Owen (2014).

References

Eunhye Song, Barry L Nelson, and Jeremy Staum. Shapley effects for global sensitivity analysis: theory and computation. SIAM/ASA Journal on Uncertainty Quantification, 4(1):1060–1083, 2016.

Art B. Owen. Sobol’ indices and shapley value. SIAM/ASA Journal on Uncertainty Quantification, 2(1):245–251, 2014.

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