statsmodels.regression.linear_model.GLS.fit

method

GLS.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

methodstr, optional

Can be “pinv”, “qr”. “pinv” uses the Moore-Penrose pseudoinverse to solve the least squares problem. “qr” uses the QR factorization.

cov_typestr, optional

See regression.linear_model.RegressionResults for a description of the available covariance estimators

cov_kwdslist or None, 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.

Returns

A RegressionResults class instance.

See also

regression.linear_model.RegressionResults, regression.linear_model.RegressionResults.get_robustcov_results

Notes

The fit method uses the pseudoinverse of the design/exogenous variables to solve the least squares minimization.