static IVLIML.from_formula(formula: str, data: pandas.DataFrame, *, weights: IVData | ndarray | DataArray | DataFrame | Series | None = None, fuller: float = 0, kappa: int | float | None = None) linearmodels.iv.model.IVLIML[source]
formula: str

Formula modified for the IV syntax described in the notes section

data: pandas.DataFrame

DataFrame containing the variables used in the formula

weights: IVData | ndarray | DataArray | DataFrame | Series | None = None

Observation weights used in estimation

fuller: float = 0

Fuller’s alpha to modify LIML estimator. Default returns unmodified LIML estimator.

kappa: int | float | None = None

Parameter value for k-class estimation. If not provided, computed to produce LIML parameter estimate.


Model instance

Return type:



The IV formula modifies the standard formula syntax to include a block of the form [endog ~ instruments] which is used to indicate the list of endogenous variables and instruments. The general structure is dependent ~ exog [endog ~ instruments] and it must be the case that the formula expressions constructed from blocks dependent ~ exog endog and dependent ~ exog instruments are both valid formulas.

A constant must be explicitly included using ‘1 +’ if required.


>>> import numpy as np
>>> from linearmodels.datasets import wage
>>> from linearmodels.iv import IVLIML
>>> data = wage.load()
>>> formula = "np.log(wage) ~ 1 + exper + exper ** 2 + brthord + [educ ~ sibs]"
>>> mod = IVLIML.from_formula(formula, data)