statsmodels.regression.linear_model.GLSAR.fit¶
- GLSAR.fit(method='pinv', cov_type='nonrobust', cov_kwds=None, use_t=None, **kwargs)¶
Full fit of the model.
The results include an estimate of covariance matrix, (whitened) residuals and an estimate of scale.
- Parameters:
- method
str
,optional
Can be “pinv”, “qr”. “pinv” uses the Moore-Penrose pseudoinverse to solve the least squares problem. “qr” uses the QR factorization.
- cov_type
str
,optional
See regression.linear_model.RegressionResults for a description of the available covariance estimators.
- cov_kwds
list
orNone
,optional
See linear_model.RegressionResults.get_robustcov_results for a description required keywords for alternative covariance estimators.
- use_tbool,
optional
Flag indicating to use the Student’s t distribution when computing p-values. Default behavior depends on cov_type. See linear_model.RegressionResults.get_robustcov_results for implementation details.
- **kwargs
Additional keyword arguments that contain information used when constructing a model using the formula interface.
- method
- Returns:
RegressionResults
The model estimation results.
See also
RegressionResults
The results container.
RegressionResults.get_robustcov_results
A method to change the covariance estimator used when fitting the model.
Notes
The fit method uses the pseudoinverse of the design/exogenous variables to solve the least squares minimization.