linearmodels.panel.results.FamaMacBethResults.predict¶
-
FamaMacBethResults.predict(exog: ndarray | DataArray | DataFrame | Series | None =
None
, *, data: DataFrame | None =None
, fitted: bool =True
, effects: bool =False
, idiosyncratic: bool =False
, missing: bool =False
) DataFrame ¶ In- and out-of-sample predictions
- Parameters:¶
- exog: ndarray | DataArray | DataFrame | Series | None =
None
¶ Exogenous values to use in out-of-sample prediction (nobs by nexog)
- data: DataFrame | None =
None
¶ DataFrame to use for out-of-sample predictions when model was constructed using a formula.
- fitted: bool =
True
¶ Flag indicating whether to include the fitted values
- effects: bool =
False
¶ Flag indicating whether to include estimated effects
- idiosyncratic: bool =
False
¶ Flag indicating whether to include the estimated idiosyncratic shock
- missing: bool =
False
¶ Flag indicating to adjust for dropped observations. if True, the values returns will have the same size as the original input data before filtering missing values
- exog: ndarray | DataArray | DataFrame | Series | None =
- Returns:¶
DataFrame containing columns for all selected output
- Return type:¶
Notes
data can only be used when the model was created using the formula interface. exog can be used for both a model created using a formula or a model specified with dependent and exog arrays.
When using exog to generate out-of-sample predictions, the variable order must match the variables in the original model.
Idiosyncratic errors and effects are not available for out-of-sample predictions.