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:¶

qfloat

Quantile must be strictly between 0 and 1

vcovstr, 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)

kernelstr, kernel to use in the kernel density estimation for the

asymptotic covariance matrix:

• epa: Epanechnikov

• cos: Cosine

• gau: Gaussian

• par: Parzene

bandwidthstr, 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)