statsmodels.regression.quantile_regression.QuantReg.fit
-
QuantReg.fit(q=0.5, vcov='robust', kernel='epa', bandwidth='hsheather', max_iter=1000, p_tol=1e-06, **kwargs)
[source] -
Solve by Iterative Weighted Least Squares
Parameters: q : float
Quantile must be between 0 and 1
vcov : string, method used to calculate the variance-covariance matrix
of the parameters. Default is
robust
:- robust : heteroskedasticity robust standard errors (as suggested in Greene 6th edition)
- iid : iid errors (as in Stata 12)
kernel : string, kernel to use in the kernel density estimation for the
asymptotic covariance matrix:
- epa: Epanechnikov
- cos: Cosine
- gau: Gaussian
- par: Parzene
bandwidth: string, Bandwidth selection method in kernel density :
estimation for asymptotic covariance estimate (full references in QuantReg docstring):
- hsheather: Hall-Sheather (1988)
- bofinger: Bofinger (1975)
- chamberlain: Chamberlain (1994)
Please login to continue.