statsmodels.regression.quantile_regression.QuantReg¶
-
class
statsmodels.regression.quantile_regression.
QuantReg
(endog, exog, **kwargs)[source]¶ Quantile Regression
Estimate a quantile regression model using iterative reweighted least squares.
- Parameters
Notes
The Least Absolute Deviation (LAD) estimator is a special case where quantile is set to 0.5 (q argument of the fit method).
The asymptotic covariance matrix is estimated following the procedure in Greene (2008, p.407-408), using either the logistic or gaussian kernels (kernel argument of the fit method).
References
General:
Birkes, D. and Y. Dodge(1993). Alternative Methods of Regression, John Wiley and Sons.
Green,W. H. (2008). Econometric Analysis. Sixth Edition. International Student Edition.
Koenker, R. (2005). Quantile Regression. New York: Cambridge University Press.
LeSage, J. P.(1999). Applied Econometrics Using MATLAB,
Kernels (used by the fit method):
Green (2008) Table 14.2
Bandwidth selection (used by the fit method):
Bofinger, E. (1975). Estimation of a density function using order statistics. Australian Journal of Statistics 17: 1-17.
Chamberlain, G. (1994). Quantile regression, censoring, and the structure of wages. In Advances in Econometrics, Vol. 1: Sixth World Congress, ed. C. A. Sims, 171-209. Cambridge: Cambridge University Press.
Hall, P., and S. Sheather. (1988). On the distribution of the Studentized quantile. Journal of the Royal Statistical Society, Series B 50: 381-391.
Keywords: Least Absolute Deviation(LAD) Regression, Quantile Regression, Regression, Robust Estimation.
Methods
fit
([q, vcov, kernel, bandwidth, max_iter, …])Solve by Iterative Weighted Least Squares
from_formula
(formula, data[, subset, drop_cols])Create a Model from a formula and dataframe.
get_distribution
(params, scale[, exog, …])Construct a random number generator for the predictive distribution.
hessian
(params)The Hessian matrix of the model.
information
(params)Fisher information matrix of model.
Initialize model components.
loglike
(params)Log-likelihood of model.
predict
(params[, exog])Return linear predicted values from a design matrix.
score
(params)Score vector of model.
whiten
(data)QuantReg model whitener does nothing: returns data.
Properties
The model degree of freedom.
The residual degree of freedom.
Names of endogenous variables.
Names of exogenous variables.