panel.smoother {latticeExtra} | R Documentation

## Plot a smoothing line with standard error bounds.

### Description

Plot a smoothing line with standard error bounds. This is based on the `stat_smooth` function from ggplot2.

### Usage

    panel.smoother(x, y, form = y ~ x, method = "loess", ...,
        se = TRUE, 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,
        ## 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 smoothing model is constructed (approximately) as `method(form, data = list(x=x, y=y), ...)`. See the Examples section for common choices.
`...` | further arguments passed on to the model function (`method`).
`se, level` | estimate standard errors on the smoother, at the given `level`, and plot these as a band.
`n` | number of equi-spaced points on which to evaluate the smooth function.
`col, col.se, lty, lwd, alpha, alpha.se, border` | graphical parameters. `col` and `alpha` apply to the smoothing line, while `col.se` and `alpha.se` apply to the shaded `se` region.
`subscripts, group.number, group.value, type, col.line, col.symbol, fill, pch, cex, font, fontface, fontfamily` | ignored.

### Details

This should work with any model function that takes a formula argument, and has a `predict` method with a `se` argument.

### Author(s)

Felix Andrews felix@nfrac.org

Based on `stat_smooth` by Hadley Wickham.

### See Also

`panel.loess`, `panel.quantile`, `stat_smooth`

### Examples

    set.seed(1)
    xy <- data.frame(x = runif(100),
                     y = rt(100, df = 5),
                     y2 = rt(100, df = 5) + 1)

    xyplot(y ~ x, xy, panel = function(...) {
           panel.xyplot(...)
           panel.smoother(..., span = 0.9)
    })

    ## per-group layers with glayer (pass `...` to get styles)
    xyplot(y + y2 ~ x, xy) +
      glayer(panel.smoother(...))

    ## natural spline with 5 degrees of freedom
    if (require("splines"))
      xyplot(y ~ x, xy) +
        layer(panel.smoother(y ~ ns(x,5), method = "lm"))

    ## thin plate regression spline with smoothness
    ## chosen by cross validation (see ?mgcv::gam)
    if (require("mgcv"))
      xyplot(y ~ x, xy) +
        layer(panel.smoother(y ~ s(x), method = "gam"))

    ## simple linear regression with standard errors:
    xyplot(y ~ x, xy) +
      layer(panel.smoother(x, y, method = "lm"), style = 2)

[Package latticeExtra version 0.6-28 Index]