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Rq

rms Package Interface to quantreg Package

Description

The Rq function is the rms front-end to the quantreg package's rq function. print and latex methods are also provided, and a fitting function RqFit is defined for use in bootstrapping, etc. Its result is a function definition.

For the print method, format of output is controlled by the user previously running options(prType="lang") where lang is "plain" (the default), "latex", or "html". For the latex method, html will actually be used of options(prType='html').

Usage

Rq(formula, tau = 0.5, data=environment(formula),
   subset, weights, na.action=na.delete,
   method = "br", model = FALSE, contrasts = NULL,
   se = "nid", hs = TRUE, x = FALSE, y = FALSE, ...)

## S3 method for class 'Rq'
print(x, digits=4, coefs=TRUE, title, ...)

## S3 method for class 'Rq'
latex(object,
           file = paste(first.word(deparse(substitute(object))),
             ".tex", sep = ""), append=FALSE,
           which, varnames, columns=65, inline=FALSE, caption=NULL, ...)

## S3 method for class 'Rq'
predict(object, ..., kint=1, se.fit=FALSE)

RqFit(fit, wallow=TRUE, passdots=FALSE)

Arguments

`formula`	model formula
`tau`	the single quantile to estimate. Unlike `rq` you cannot estimate more than one quantile at one model fitting.
`data,subset,weights,na.action,method,model,contrasts,se,hs`	see `rq`
`x`	set to `TRUE` to store the design matrix with the fit. For `print` is an `Rq` object.
`y`	set to `TRUE` to store the response vector with the fit
`...`	other arguments passed to one of the `rq` fitting routines. For `latex.Rq` these are optional arguments passed to `latexrms`. Ignored for `print.Rq`. For `predict.Rq` this is usually just a `newdata` argument.
`digits`	number of significant digits used in formatting results in `print.Rq`.
`coefs`	specify `coefs=FALSE` to suppress printing the table of model coefficients, standard errors, etc. Specify `coefs=n` to print only the first `n` regression coefficients in the model.
`title`	a character string title to be passed to `prModFit`
`object`	an object created by `Rq`
`file,append,which,varnames,columns,inline,caption`	see `latexrms`
`kint`	ignored
`se.fit`	set to `TRUE` to obtain standard errors of predicted quantiles
`fit`	an object created by `Rq`
`wallow`	set to `TRUE` if `weights` are allowed in the current context.
`passdots`	set to `TRUE` if ... may be passed to the fitter

Value

Rq returns a list of class "rms", "lassorq" or "scadrq", "Rq", and "rq". RqFit returns a function definition. latex.Rq returns an object of class "latex".

Note

The author and developer of methodology in the quantreg package is Roger Koenker.

Author(s)

Frank Harrell

Examples

## Not run: 
set.seed(1)
n <- 100
x1 <- rnorm(n)
y <- exp(x1 + rnorm(n)/4)
dd <- datadist(x1); options(datadist='dd')
fq2 <- Rq(y ~ pol(x1,2))
anova(fq2)
fq3 <- Rq(y ~ pol(x1,2), tau=.75)
anova(fq3)
pq2 <- Predict(fq2, x1)
pq3 <- Predict(fq3, x1)
p <- rbind(Median=pq2, Q3=pq3)
plot(p, ~ x1 | .set.)
# For superpositioning, with true curves superimposed
a <- function(x, y, ...) {
 x <- unique(x)
 col <- trellis.par.get('superpose.line')$col
 llines(x, exp(x), col=col[1], lty=2)
 llines(x, exp(x + qnorm(.75)/4), col=col[2], lty=2)
}
plot(p, addpanel=a)

## End(Not run)

rms

Regression Modeling Strategies

v6.2-0

GPL (>= 2)

Authors

Frank E Harrell Jr <fh@fharrell.com>

Initial release

2021-03-17

Rq