linearmodels.panel.model.BetweenOLS.predict

BetweenOLS.predict(self, params: Union[numpy.ndarray, xarray.core.dataarray.DataArray, pandas.core.frame.DataFrame, pandas.core.series.Series], *, exog: Union[linearmodels.panel.data.PanelData, numpy.ndarray, xarray.core.dataarray.DataArray, pandas.core.frame.DataFrame, pandas.core.series.Series, NoneType] = None, data: Union[linearmodels.panel.data.PanelData, numpy.ndarray, xarray.core.dataarray.DataArray, pandas.core.frame.DataFrame, pandas.core.series.Series, NoneType] = None, eval_env: int = 4) → pandas.core.frame.DataFrame

Predict values for additional data

Parameters
paramsarray_like

Model parameters (nvar by 1)

exogarray_like

Exogenous regressors (nobs by nvar)

dataDataFrame

Values to use when making predictions from a model constructed from a formula

eval_envint

Depth of use when evaluating formulas using Patsy.

Returns
DataFrame

Fitted values from supplied data and parameters

Notes

If data is not None, then exog must be None. Predictions from models constructed using formulas can be computed using either exog, which will treat these are arrays of values corresponding to the formula-processed data, or using data which will be processed using the formula used to construct the values corresponding to the original model specification.

Return type

DataFrame