linearmodels.panel.data.PanelData.demean¶
- PanelData.demean(group: Literal['entity', 'time', 'both'], *, return_panel: Literal[False]) ndarray [source]¶
- PanelData.demean(group: Literal['entity', 'time', 'both'] = 'entity', weights: PanelData | None = None, return_panel: Literal[True] = True, low_memory: bool = False) PanelData
- PanelData.demean(group: Literal['entity', 'time', 'both'], weights: PanelData | None, return_panel: Literal[False]) ndarray
- PanelData.demean(group: Literal['entity', 'time', 'both'] = 'entity', weights: PanelData | None = None, return_panel: Literal[True] = True, low_memory: bool = False) PanelData
Demeans data by either entity or time group
- Parameters:
- group{“entity”, “time”, “both”}
Group to use in demeaning
- weights
PanelData
Weights to implement weighted averaging
- return_panelbool
Flag indicating to return a PanelData object. If False, a 2-d NumPy representation of the panel is returned
- low_memorybool
Flag indicating whether to use a low memory implementation that avoids constructing dummy variables. Only relevant when group is “both”
- Returns:
PanelData
Demeaned data according to type
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.
- Return type:
PanelData | Float64Array