linearmodels.panel.model.PooledOLS.from_formula

classmethod PooledOLS.from_formula(formula, data, *, weights=None, check_rank=True)[source]

Create a model from a formula

Parameters
formulastr

Formula to transform into model. Conforms to formulaic formula rules.

dataarray_like

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: array_like

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_rankbool

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
PooledOLS

Model specified using the formula

Notes

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

Examples

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

PooledOLS