R: Preprocessing fitting method for QR

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

### See Also

`rq.fit.pfn`, `boot.rq.pxy`

[Package quantreg version 5.93 Index]