panel.quantile {latticeExtra} R Documentation

## Plot a quantile regression line with standard error bounds.

### Description

Plot a quantile regression line with standard error bounds, using the quantreg package. This is based on the `stat_quantile` function from ggplot2.

### Usage

```panel.quantile(x, y, form = y ~ x, method = "rq", ...,
tau = 0.5, ci = FALSE, ci.type = "default", level = 0.95,
n = 100, col = plot.line\$col, col.se = col,
lty = plot.line\$lty, lwd = plot.line\$lwd,
alpha = plot.line\$alpha, alpha.se = 0.25, border = NA,
superpose = FALSE,
## ignored: ##
subscripts, group.number, group.value,
type, col.line, col.symbol, fill,
pch, cex, font, fontface, fontfamily)
```

### Arguments

 `x, y` data points. If these are missing, they will be looked for in the environment of `form`. So in many cases you can skip these if passing `form`. In fact, for convenience, the formula can be passed as the first argument (i.e. `x`). `form, method` the model is constructed (approximately) as `method(form, tau = tau, data = list(x=x, y=y), ...)`. See the Examples section for common choices. `...` further arguments passed on to the model function (`method`), typically `rq`. `tau` p values for the quantiles to estimate. Note: only one value for `tau` can be specified if estimating confidence intervals with `ci`. `ci, ci.type, level` estimate a confidence interval at level `level` using the method `ci.type`; see `predict.rq`. `n` number of equi-spaced points on which to evaluate the function. `col, col.se, lty, lwd, alpha, alpha.se, border` graphical parameters. `col` and `alpha` apply to the line(s), while `col.se` and `alpha.se` apply to the shaded `ci` region. `superpose` if `TRUE`, plot each quantile line (`tau`) in a different style (using `trellis.par.get("superpose.line")`). ```subscripts, group.number, group.value, type, col.line, col.symbol, fill, pch, cex, font, fontface, fontfamily``` ignored.

### Details

It is recommended to look at `vignette("rq",package="quantreg")`.

### Author(s)

Felix Andrews felix@nfrac.org

Based on `stat_quantile` by Hadley Wickham.

`rq`, `panel.smoother`, `stat_quantile`

### Examples

```library("quantreg")

set.seed(1)
xy <- data.frame(x = runif(100), y = rt(100, df = 5))
xyplot(y ~ x, xy) +
layer(panel.quantile(x, y, tau = c(.95, .5, .05)))

if (require("splines")) {
xyplot(y ~ x, xy) +
layer(panel.quantile(y ~ ns(x, 3), tau = 0.9))

xyplot(y ~ x, xy) +
layer(panel.quantile(y ~ ns(x, 3), tau = 0.9, ci = TRUE))
}

xyplot(y ~ x, xy) +
layer(panel.quantile(x, y, tau = c(.5, .9, .1), superpose = TRUE))
update(trellis.last.object(),
auto.key = list(text = paste(c(50,90,10), "% quantile"),
points = FALSE, lines = TRUE))

## seems not to work...
#xyplot(y ~ x, xy) +
#  layer(panel.quantile(y ~ qss(x, lambda=1), method = "rqss"))
```
[Package latticeExtra version 0.6-25 Index]