R: rms Package Interface to quantreg Package

Rq {rms} | R Documentation

## 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, 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

### See Also

`rq`, `prModFit`, `orm`

### 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)

[Package rms version 5.1-1 Index]