OLS.fit()
statsmodels.regression.linear_model.OLS.fit
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OLS.fit(method='pinv', cov_type='nonrobust', cov_kwds=None, use_t=None, **kwargs)
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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 estimatorscov_kwds : list or None, optional
See
linear_model.RegressionResults.get_robustcov_results
for a description required keywords for alternative covariance estimatorsuse_t : bool, 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.
© 2009–2012 Statsmodels Developers
© 2006–2008 Scipy Developers
© 2006 Jonathan E. Taylor
Licensed under the 3-clause BSD License.
http://www.statsmodels.org/stable/generated/statsmodels.regression.linear_model.OLS.fit.html