Information-Theoretic Performance Measures
Information-Theoretic Performance MeasuresΒΆ
HydroBench allows the computation of multi-dimensional entropies (H(.)), Mutual Information MI(.,.) and Tranfer Entropy - TE represented as MI(.,.|.). By using these metrics, two model diagnostics can be undertaken:
understanding the tradeoffs between predictive and functional model performances.
understanding model internal functions that lead to the predictive performance using Process Networks.
MI is used as a predictive performance metrics while TE is used as an indicator of model functional performance.
The computation of MI and TE requires different joint and marginal probabilities of the various flux and store hydrological variables referred in the input table header. In order to compute these probabilities, HydroBench employed histogram based probability estimation.
Table 3 shows the syntax, description and equations of the Information-theoretic metrics. For their implementation, please refere to the example notebook.
