Add a smoothed conditional mean.

Usage

geom_smooth(mapping = NULL, data = NULL, stat = "smooth", position = "identity", 
  ...)

Arguments

mapping

The aesthetic mapping, usually constructed with aes or aes_string. Only needs to be set at the layer level if you are overriding the plot defaults.

data

A layer specific dataset - only needed if you want to override the plot defaults.

stat

The statistical transformation to use on the data for this layer.

position

The position adjustment to use for overlappling points on this layer

...

other arguments passed on to layer. This can include aesthetics whose values you want to set, not map. See layer for more details.

Examples

# See stat_smooth for examples of using built in model fitting
# if you need some more flexible, this example shows you how to
# plot the fits from any model of your choosing
qplot(wt, mpg, data=mtcars, colour=factor(cyl))



model <- lm(mpg ~ wt + factor(cyl), data=mtcars)
grid <- with(mtcars, expand.grid(
  wt = seq(min(wt), max(wt), length = 20),
  cyl = levels(factor(cyl))
))

grid$mpg <- stats::predict(model, newdata=grid)

qplot(wt, mpg, data=mtcars, colour=factor(cyl)) + geom_line(data=grid)



# or with standard errors

err <- stats::predict(model, newdata=grid, se = TRUE)
grid$ucl <- err$fit + 1.96 * err$se.fit
grid$lcl <- err$fit - 1.96 * err$se.fit

qplot(wt, mpg, data=mtcars, colour=factor(cyl)) +
  geom_smooth(aes(ymin = lcl, ymax = ucl), data=grid, stat="identity")

See also