linearmodels.system.model.IV3SLS.fit¶
-
IV3SLS.fit(*, method=
None, full_cov=True, iterate=False, iter_limit=100, tol=1e-06, cov_type='robust', **cov_config)¶ Estimate model parameters
- Parameters:¶
- method : {None, "gls", "ols"}¶
Estimation method. Default auto selects based on regressors, using OLS only if all regressors are identical. The other two arguments force the use of GLS or OLS.
- full_cov : bool¶
Flag indicating whether to utilize information in correlations when estimating the model with GLS
- iterate : bool¶
Flag indicating to iterate GLS until convergence of iter limit iterations have been completed
- iter_limit : int¶
Maximum number of iterations for iterative GLS
- tol : float¶
Tolerance to use when checking for convergence in iterative GLS
- cov_type : str¶
Name of covariance estimator. Valid options are
”unadjusted”, “homoskedastic” - Classic covariance estimator
”robust”, “heteroskedastic” - Heteroskedasticity robust covariance estimator
”kernel” - Allows for heteroskedasticity and autocorrelation
”clustered” - Allows for 1 and 2-way clustering of errors (Rogers).
- **cov_config :
bool Additional parameters to pass to covariance estimator. All estimators support debiased which employs a small-sample adjustment
- Returns:¶
results – Estimation results
- Return type:¶