| rq.fit.ppro {quantreg} | R Documentation |
Preprocessing fitting method for QR
Description
Preprocessing method for fitting quantile regression models that exploits the fact that adjacent tau's should have nearly the same sign vectors for residuals.
Usage
rq.fit.ppro(x, y, tau, weights = NULL, Mm.factor = 0.8, eps = 1e-06, ...)
Arguments
x |
Design matrix |
y |
Response vector |
tau |
quantile vector of interest |
weights |
case weights |
Mm.factor |
constant determining initial sample size |
eps |
Convergence tolerance |
... |
Other arguments |
Details
See references for further details.
Value
Returns a list with components:
coefficients |
Matrix of coefficient estimates |
residuals |
Matrix of residual estimates |
rho |
vector of objective function values |
weights |
vector of case weights |
Author(s)
Blaise Melly and Roger Koenker
References
Chernozhukov, V. I. Fernandez-Val and B. Melly, Fast Algorithms for the Quantile Regression Process, 2020, Empirical Economics.,
Portnoy, S. and R. Koenker, The Gaussian Hare and the Laplacian Tortoise, Statistical Science, (1997) 279-300