GLS.fit()

statsmodels.regression.linear_model.GLS.fit

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:

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登录查看完整内容 ← → Copyright©2021 w3cschool编程狮\|闽ICP备15016281号-3\|闽公网安备35020302033924号违法和不良信息举报电话：173-0602-2364\|举报邮箱：jubao@eeedong.com 意见反馈 X 意见反馈：联系方式：查看完整版笔记违规举报 X 广告等垃圾信息不友善内容违反法律法规的内容不宜公开讨论的政治内容其他

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登录查看完整内容