stat_plsmo | R Documentation |
Automatically selects iter=0
for lowess
if y
is binary, otherwise uses iter=3
.
stat_plsmo(
mapping = NULL,
data = NULL,
geom = "smooth",
position = "identity",
n = 80,
fullrange = FALSE,
span = 2/3,
fun = function(x) x,
na.rm = FALSE,
show.legend = NA,
inherit.aes = TRUE,
...
)
mapping , data , geom , position , show.legend , inherit.aes |
see ggplot2 documentation |
n |
number of points to evaluate smoother at |
fullrange |
should the fit span the full range of the plot, or just the data |
span |
see |
fun |
a function to transform smoothed |
na.rm |
If |
... |
other arguments are passed to smoothing function |
a data.frame with additional columns
y |
predicted value |
lowess
for loess
smoother.
require(ggplot2)
c <- ggplot(mtcars, aes(qsec, wt))
c + stat_plsmo()
c + stat_plsmo() + geom_point()
c + stat_plsmo(span = 0.1) + geom_point()
# Smoothers for subsets
c <- ggplot(mtcars, aes(y=wt, x=mpg)) + facet_grid(. ~ cyl)
c + stat_plsmo() + geom_point()
c + stat_plsmo(fullrange = TRUE) + geom_point()
# Geoms and stats are automatically split by aesthetics that are factors
c <- ggplot(mtcars, aes(y=wt, x=mpg, colour=factor(cyl)))
c + stat_plsmo() + geom_point()
c + stat_plsmo(aes(fill = factor(cyl))) + geom_point()
c + stat_plsmo(fullrange=TRUE) + geom_point()
# Example with logistic regression
data("kyphosis", package="rpart")
qplot(Age, as.numeric(Kyphosis) - 1, data = kyphosis) + stat_plsmo()
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