PyMCForecastModel.print_coefficients#

PyMCForecastModel.print_coefficients(labels, round_to=None)[source]#

Print posterior means and HDIs of the model’s scalar parameters.

Forecasting-model parameters do not map onto the patsy design-matrix labels, so those are ignored; every scalar variable in the fitted posterior is reported instead. Time-varying latents are skipped.

Parameters:

  • labels (list[str]) – Design-matrix labels; ignored by forecasting models.

  • round_to (int | None) – Number of significant figures to round to. Defaults to None, in which case 2 significant figures are used.

Return type:

None