gluonts.ev.stats module#

gluonts.ev.stats.absolute_error(data: Dict[str, numpy.ndarray], forecast_type: str) → numpy.ndarray[source]#

gluonts.ev.stats.absolute_label(data: Dict[str, numpy.ndarray]) → numpy.ndarray[source]#

gluonts.ev.stats.absolute_percentage_error(data: Dict[str, numpy.ndarray], forecast_type: str) → numpy.ndarray[source]#

gluonts.ev.stats.absolute_scaled_error(data: Dict[str, numpy.ndarray], forecast_type: str) → numpy.ndarray[source]#

gluonts.ev.stats.coverage(data: Dict[str, numpy.ndarray], q: float) → numpy.ndarray[source]#

gluonts.ev.stats.error(data: Dict[str, numpy.ndarray], forecast_type: str) → numpy.ndarray[source]#

gluonts.ev.stats.num_masked_target_values(data: Dict[str, numpy.ndarray]) → numpy.ndarray[source]#

gluonts.ev.stats.quantile_loss(data: Dict[str, numpy.ndarray], q: float) → numpy.ndarray[source]#

gluonts.ev.stats.scaled_interval_score(data: Dict[str, numpy.ndarray], alpha: float) → numpy.ndarray[source]#

gluonts.ev.stats.scaled_quantile_loss(data: Dict[str, numpy.ndarray], q: float) → numpy.ndarray[source]#

gluonts.ev.stats.squared_error(data: Dict[str, numpy.ndarray], forecast_type: str) → numpy.ndarray[source]#

gluonts.ev.stats.symmetric_absolute_percentage_error(data: Dict[str, numpy.ndarray], forecast_type: str) → numpy.ndarray[source]#