3.9.4. statsmodels.regression.quantile_regression

Quantile regression model

Model parameters are estimated using iterated reweighted least squares. The asymptotic covariance matrix estimated using kernel density estimation.

Author: Vincent Arel-Bundock License: BSD-3 Created: 2013-03-19

The original IRLS function was written for Matlab by Shapour Mohammadi, University of Tehran, 2008 (shmohammadi@gmail.com), with some lines based on code written by James P. Lesage in Applied Econometrics Using MATLAB(1999).PP. 73-4. Translated to python with permission from original author by Christian Prinoth (christian at prinoth dot name).

3.9.4.1. Functions

bofinger(n, q)
chain_dot(*arrs) Returns the dot product of the given matrices.
chamberlain(n, q[, alpha])
hall_sheather(n, q[, alpha])

3.9.4.2. Classes

QuantReg(endog, exog, **kwargs) Quantile Regression
QuantRegResults(model, params[, ...]) Results instance for the QuantReg model
RegressionModel(endog, exog, **kwargs) Base class for linear regression models.
RegressionResults(model, params[, ...]) This class summarizes the fit of a linear regression model.
RegressionResultsWrapper(results)