geom_lm: Linear Model Displays

In ggformula: Formula Interface to the Grammar of Graphics

Linear Model Displays

Description

Adds linear model fits to plots. geom_lm() and stat_lm() are essentially equivalent. Use geom_lm() unless you want a non-standard geom.

Usage

stat_lm(
  mapping = NULL,
  data = NULL,
  geom = "lm",
  position = "identity",
  interval = c("none", "prediction", "confidence"),
  level = 0.95,
  formula = y ~ x,
  lm.args = list(),
  backtrans = identity,
  ...,
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE
)

geom_lm(
  mapping = NULL,
  data = NULL,
  stat = "lm",
  position = "identity",
  interval = c("none", "prediction", "confidence"),
  level = 0.95,
  formula = y ~ x,
  lm.args = list(),
  backtrans = identity,
  ...,
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE
)

Arguments

mapping	Set of aesthetic mappings created by aes(). If specified and inherit.aes = TRUE (the default), it is combined with the default mapping at the top level of the plot. You must supply mapping if there is no plot mapping.
data	The data to be displayed in this layer. There are three options: If NULL, the default, the data is inherited from the plot data as specified in the call to ggplot(). A data.frame, or other object, will override the plot data. All objects will be fortified to produce a data frame. See fortify() for which variables will be created. A function will be called with a single argument, the plot data. The return value must be a data.frame, and will be used as the layer data. A function can be created from a formula (e.g. ~ head(.x, 10)).
geom, stat	Use to override the default connection between geom_lm and stat_lm.
position	Position adjustment, either as a string naming the adjustment (e.g. "jitter" to use position_jitter), or the result of a call to a position adjustment function. Use the latter if you need to change the settings of the adjustment.
interval	One of "none", "confidence" or "prediction".
level	The level used for confidence or prediction intervals
formula	a formula describing the model in terms of y (response) and x (predictor).
lm.args	A list of arguments supplied to lm() when performing the fit.
backtrans	a function that transforms the response back to the original scale when the formula includes a transformation on y.
...	Other arguments passed on to layer(). These are often aesthetics, used to set an aesthetic to a fixed value, like colour = "red" or size = 3. They may also be parameters to the paired geom/stat.
na.rm	If FALSE, the default, missing values are removed with a warning. If TRUE, missing values are silently removed.
show.legend	logical. Should this layer be included in the legends? NA, the default, includes if any aesthetics are mapped. FALSE never includes, and TRUE always includes. It can also be a named logical vector to finely select the aesthetics to display.
inherit.aes	If FALSE, overrides the default aesthetics, rather than combining with them. This is most useful for helper functions that define both data and aesthetics and shouldn't inherit behaviour from the default plot specification, e.g. borders().

Details

Stat calculation is performed by the (currently undocumented) predictdf. Pointwise confidence or prediction bands are calculated using the predict() method.

See Also

lm() for details on linear model fitting.

Examples

ggplot(data = mosaicData::KidsFeet, aes(y = length, x = width, color = sex)) +
  geom_lm() +
  geom_point()
ggplot(data = mosaicData::KidsFeet, aes(y = length, x = width, color = sex)) +
  geom_lm(interval = "prediction", color = "skyblue") +
  geom_lm(interval = "confidence") +
  geom_point() +
  facet_wrap(~sex)
# non-standard display
ggplot(data = mosaicData::KidsFeet, aes(y = length, x = width, color = sex)) +
  stat_lm(aes(fill = sex),
    color = NA, interval = "confidence", geom = "ribbon",
    alpha = 0.2
  ) +
  geom_point() +
  facet_wrap(~sex)
ggplot(mpg, aes(displ, hwy)) +
  geom_lm(
    formula = log(y) ~ poly(x, 3), backtrans = exp,
    interval = "prediction", fill = "skyblue"
  ) +
  geom_lm(
    formula = log(y) ~ poly(x, 3), backtrans = exp, interval = "confidence",
    color = "red"
  ) +
  geom_point()

ggformula documentation built on Nov. 9, 2023, 5:08 p.m.