linearmodels.panel.data.PanelData.demean¶

PanelData.demean(group: 'entity' | 'time' | 'both', *, return_panel: False) → ndarray[tuple[int, ...], dtype[float64]][source]¶

PanelData.demean(group: 'entity' | 'time' | 'both' = 'entity', weights: PanelData | None = None, return_panel: True = True, low_memory: bool = False) → PanelData

PanelData.demean(group: 'entity' | 'time' | 'both', weights: PanelData | None, return_panel: False) → ndarray[tuple[int, ...], dtype[float64]]

Demeans data by either entity or time group

Parameters:¶

group: 'entity' | 'time' | 'both'¶

group: 'entity' | 'time' | 'both' = 'entity'

Group to use in demeaning

weights: PanelData | None = None

weights: PanelData | None

Weights to implement weighted averaging

return_panel: False¶

return_panel: True = True

Flag indicating to return a PanelData object. If False, a 2-d NumPy representation of the panel is returned

low_memory: bool = False

Flag indicating whether to use a low memory implementation that avoids constructing dummy variables. Only relevant when group is “both”

Returns:¶

Demeaned data according to type

Return type:¶

linearmodels.panel.data.PanelData

Notes

If weights are provided, the values returned will be scaled by the square root of the weights so that they can be used in WLS estimation.