linearmodels.iv.model._OLS¶

class linearmodels.iv.model._OLS(dependent: IVData | ndarray | DataArray | DataFrame | Series, exog: IVData | ndarray | DataArray | DataFrame | Series, *, weights: IVData | ndarray | DataArray | DataFrame | Series | None = None)[source]¶

Computes OLS estimates when required

Private class used when model reduces to OLS. Should use the statsmodels version when neeeding a supported public API.

Parameters:¶

dependent: IVData | ndarray | DataArray | DataFrame | Series¶

Endogenous variables (nobs by 1)

exog: IVData | ndarray | DataArray | DataFrame | Series¶

Exogenous regressors (nobs by nexog)

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

Observation weights used in estimation

Notes

Uses IV2SLS internally by setting endog and instruments to None. Uses IVLIML with kappa=0 to estimate OLS models.

See also

statsmodels.regression.linear_model.OLS, statsmodels.regression.linear_model.GLS

Methods

estimate_parameters(x, y, z, kappa)	Parameter estimation without error checking
fit(*[, cov_type, debiased])	Estimate model parameters
from_formula(formula, data, *[, weights, ...])
predict(params, *[, exog, endog, data, eval_env])	Predict values for additional data
resids(params)	Compute model residuals
wresids(params)	Compute weighted model residuals

Properties

formula	Formula used to create the model
has_constant	Flag indicating the model includes a constant or equivalent
isnull	Locations of observations with missing values
notnull	Locations of observations included in estimation