linearmodels.panel.model.RandomEffects.from_formula¶

Create a model from a formula

Parameters:¶

formula: str¶: Formula to transform into model. Conforms to formulaic formula rules.
data: PanelData | ndarray | DataArray | DataFrame | Series¶: Data structure that can be coerced into a PanelData. In most cases, this should be a multi-index DataFrame where the level 0 index contains the entities and the level 1 contains the time.
weights: PanelData | ndarray | DataArray | DataFrame | Series | None = None¶: Weights to use in estimation. Assumes residual variance is proportional to inverse of weight to that the residual times the weight should be homoskedastic.
check_rank: bool = True¶: Flag indicating whether to perform a rank check on the exogenous variables to ensure that the model is identified. Skipping this check can reduce the time required to validate a model specification. Results may be numerically unstable if this check is skipped and the matrix is not full rank.

Returns:¶

Model specified using the formula

Return type:¶

linearmodels.panel.model.RandomEffects

Notes

Unlike standard formula syntax, it is necessary to explicitly include a constant using the constant indicator (1)

Examples

>>> from linearmodels import RandomEffects
>>> from linearmodels.panel import generate_panel_data
>>> panel_data = generate_panel_data()
>>> mod = RandomEffects.from_formula("y ~ 1 + x1", panel_data.data)
>>> res = mod.fit()