linearmodels.system.model.IVSystemGMM.fit¶
-
IVSystemGMM.fit(*, 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
- 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
- **cov_config: bool | float¶
Additional parameters to pass to covariance estimator. All estimators support debiased which employs a small-sample adjustment
- iter_limit: int =
- Returns:¶
Estimation results
- Return type:¶