geom_quantile {animint2}  R Documentation 
This can be used as a continuous analogue of a geom_boxplot.
geom_quantile( mapping = NULL, data = NULL, stat = "quantile", position = "identity", ..., lineend = "butt", linejoin = "round", linemitre = 1, na.rm = FALSE, show.legend = NA, inherit.aes = TRUE ) stat_quantile( mapping = NULL, data = NULL, geom = "quantile", position = "identity", ..., quantiles = c(0.25, 0.5, 0.75), formula = NULL, method = "rq", method.args = list(), na.rm = FALSE, show.legend = NA, inherit.aes = TRUE )
mapping 
Set of aesthetic mappings created by 
data 
The data to be displayed in this layer. There are three options: If A A 
position 
Position adjustment, either as a string, or the result of a call to a position adjustment function. 
... 
other arguments passed on to 
lineend 
Line end style (round, butt, square) 
linejoin 
Line join style (round, mitre, bevel) 
linemitre 
Line mitre limit (number greater than 1) 
na.rm 
If 
show.legend 
logical. Should this layer be included in the legends?

inherit.aes 
If 
geom, stat 
Use to override the default connection between

quantiles 
conditional quantiles of y to calculate and display 
formula 
formula relating y variables to x variables 
method 
Quantile regression method to use. Currently only supports

method.args 
List of additional arguments passed on to the modelling
function defined by 
geom_quantile
understands the following aesthetics (required aesthetics are in bold):
x
y
alpha
colour
linetype
size
weight
quantile of distribution
m < ggplot(mpg, aes(displ, 1 / hwy)) + geom_point() m + geom_quantile() m + geom_quantile(quantiles = 0.5) q10 < seq(0.05, 0.95, by = 0.05) m + geom_quantile(quantiles = q10) # You can also use rqss to fit smooth quantiles m + geom_quantile(method = "rqss") # Note that rqss doesn't pick a smoothing constant automatically, so # you'll need to tweak lambda yourself m + geom_quantile(method = "rqss", lambda = 0.1) # Set aesthetics to fixed value m + geom_quantile(colour = "red", size = 2, alpha = 0.5)