[Hierarchical] Allow computing projection based on a non-Euclidean norm #2961
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Can we add tests to be sure that the new introduced projection matrix is indeed projecting into the subspace of reconciled samples? Places where these tests could be added are: |
melopeo
reviewed
Aug 15, 2023
melopeo
reviewed
Aug 15, 2023
| @@ -109,6 +127,12 @@ class DeepVARHierarchicalEstimator(DeepVAREstimator): | |||
| Length of the prediction horizon | |||
| S | |||
| Summation or aggregation matrix. | |||
| D | |||
| Positive definite matrix (typically a diagonal matrix). Optional. | |||
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Should we specify "symmetric" positive definite matrix?
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melopeo
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Aug 15, 2023
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Issue #, if available:
Description of changes:
Currently the forecasts are reconciled by projecting them on to the feasible set based on the Euclidean norm. Sometimes it is desirable to weigh the distances (errors) between the unreconciled and reconciled forecasts differently for each level (because there are more number of terms for the bottom level compared to the top level).
This PR adds an option to provide such weights via a diagonal matrix.
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Please tag this pr with at least one of these labels to make our release process faster: BREAKING, new feature, bug fix, other change, dev setup