*, iter_limit: int = 2, tol: float = 1e-06, initial_weight: ndarray | None = None, cov_type: str = 'robust', **cov_config: bool | float) linearmodels.system.results.GMMSystemResults[source]

Estimate model parameters

iter_limit: int = 2

Maximum number of iterations for iterative GLS

tol: float = 1e-06

Tolerance to use when checking for convergence in iterative GLS

initial_weight: ndarray | None = None

Initial weighting matrix to use in the first step. If not specified, uses the average outer-product of the set containing the exogenous variables and instruments.

cov_type: str = 'robust'

Name of covariance estimator. Valid options are

  • ”unadjusted”, “homoskedastic” - Classic covariance estimator

  • ”robust”, “heteroskedastic” - Heteroskedasticity robust covariance estimator


Additional parameters to pass to covariance estimator. All estimators support debiased which employs a small-sample adjustment


Estimation results

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