quantreg: boot.rq.pwxy – R documentation

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boot.rq.pwxy

Preprocessing weighted bootstrap method

Description

Bootstrap method exploiting preprocessing strategy to reduce computation time for large problem. In contrast to boot.rq.pxy which uses the classical multinomial sampling scheme and is coded in R, this uses the exponentially weighted bootstrap scheme and is coded in fortran and consequently is considerably faster in larger problems.

Usage

boot.rq.pwxy(x, y, tau, coef, R = 200, m0 = NULL, eps = 1e-06, ...)

Arguments

`x`	Design matrix
`y`	response vector
`tau`	quantile of interest
`coef`	point estimate of fitted object
`R`	the number of bootstrap replications desired.
`m0`	constant to determine initial sample size, defaults to sqrt(n*p) but could use some further tuning...
`eps`	tolerance for convergence of fitting algorithm
`...`	other parameters not yet envisaged.

Details

The fortran implementation is quite similar to the R code for boot.rq.pxy except that there is no multinomial sampling. Instead rexp(n) weights are used.

Value

returns a list with elements:

coefficientsa matrix of dimension ncol(x) by R
nit a 5 by m matrix of iteration counts
info an m-vector of convergence flags

Author(s)

Blaise Melly and Roger Koenker

References

Chernozhukov, V. I. Fernandez-Val and B. Melly, Fast Algorithms for the Quantile Regression Process, 2019, arXiv, 1909.05782,

Portnoy, S. and R. Koenker, The Gaussian Hare and the Laplacian Tortoise, Statistical Science, (1997) 279-300

Roger Koenker [cre, aut], Stephen Portnoy [ctb] (Contributions to Censored QR code), Pin Tian Ng [ctb] (Contributions to Sparse QR code), Blaise Melly [ctb] (Contributions to preprocessing code), Achim Zeileis [ctb] (Contributions to dynrq code essentially identical to his dynlm code), Philip Grosjean [ctb] (Contributions to nlrq code), Cleve Moler [ctb] (author of several linpack routines), Yousef Saad [ctb] (author of sparskit2), Victor Chernozhukov [ctb] (contributions to extreme value inference code), Ivan Fernandez-Val [ctb] (contributions to extreme value inference code), Brian D Ripley [trl, ctb] (Initial (2001) R port from S (to my everlasting shame -- how could I have been so slow to adopt R!) and for numerous other suggestions and useful advice)

Initial release