A Python wrapper for quantreg in R programming language.
>>> from quantreg.qr import quantreg
>>> import statsmodels.api as sm
>>> import pandas as pd
>>> data = pd.DataFrame(sm.datasets.engel.load_pandas().data)
>>> qr_model = quantreg()
>>> fit = qr_model.fit_pogs(data[['foodexp', ]], data['income'], tau = 0.3)
>>> print(fit)
# {'Coefficients': {'Intercept': 11.195980483128324, 'foodexp': 1.378005107774296}, 'Time (s)': 0.01637101173400879}Documentation ------------
Read the docs at https://cran.r-project.org/web/packages/quantreg/quantreg.pdf
>>> # to use pogs, add method = "pogs" parameter
>>> fit = qr_model.fit_pogs(data[['foodexp', ]], data['income'], tau = 0.3, method = "pogs")