rq.fit.ppro: Preprocessing fitting method for QR

In quantreg: Quantile Regression

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

See Also

rq.fit.pfn, boot.rq.pxy

quantreg documentation built on Aug. 19, 2023, 5:09 p.m.