Preprocessing method for fitting quantile regression models that exploits the fact that adjacent tau's should have nearly the same sign vectors for residuals.
rq.fit.ppro(x, y, tau, weights = NULL, Mm.factor = 0.8, eps = 1e-06, ...)Returns a list with components:
Matrix of coefficient estimates
Matrix of residual estimates
vector of objective function values
vector of case weights
Design matrix
Response vector
quantile vector of interest
case weights
constant determining initial sample size
Convergence tolerance
Other arguments
Blaise Melly and Roger Koenker
See references for further details.
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
rq.fit.pfn, boot.rq.pxy