evaluate). For forecasters, the general model is that it can look at everything it has seen, so using a negative
fhwill not result in proper forecasts, evaluation will be too over-optimistic.
@ilyasmoutawwakil, v.0.8.0 added framework support for multivariate forecasting, i.e., tests, input/output checks etc. In that releas version, only two concrete learners are available - the
ColumnEnsembleForecaster (which allows you to apply different forecasters to different columns, or the same forecaster to all columns). These were mainly used for testing and framework development. Generally, you can find the multivariate forecasters by searching the
scitype:y tag for
all_estimators. Currently, a number of multivariate forecasters are under development or under review: pipeline, grid search alan-turing-institute/sktime#1376 alan-turing-institute/sktime#856; vector autoregression alan-turing-institute/sktime#1083.
There's a few more forecasters that could be extended to multivariate, if you want to pick up any? alan-turing-institute/sktime#1364.