linearmodels.panel.results.RandomEffectsResults.predict¶
-
RandomEffectsResults.predict(exog=
None
, *, data=None
, fitted=True
, effects=False
, idiosyncratic=False
, missing=False
)¶ In- and out-of-sample predictions
- Parameters:¶
- exog : array_like¶
Exogenous values to use in out-of-sample prediction (nobs by nexog)
- data : DataFrame¶
DataFrame to use for out-of-sample predictions when model was constructed using a formula.
- fitted : bool¶
Flag indicating whether to include the fitted values
- effects : bool¶
Flag indicating whether to include estimated effects
- idiosyncratic : bool¶
Flag indicating whether to include the estimated idiosyncratic shock
- missing : bool¶
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
- Returns:¶
DataFrame containing columns for all selected output
- Return type:¶
DataFrame
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.