RandomEffectsResults.predict(exog=None, *, data=None, fitted=True, effects=False, idiosyncratic=False, missing=False)

In- and out-of-sample predictions

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


DataFrame containing columns for all selected output

Return type:



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.