Description Usage Arguments Aesthetics Computed variables Examples
View source: R/geomquantile.r
This fits a quantile regression to the data and draws the fitted quantiles
with lines. This is as a continuous analogue to geom_boxplot
.
1 2 3 4 5 6 7 8  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 
geomquantile
quantile of distribution
1 2 3 4 5 6 7 8 9 10 11 12 13 14  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)

Loading required package: SparseM
Attaching package: 'SparseM'
The following object is masked from 'package:base':
backsolve
Smoothing formula not specified. Using: y ~ x
Smoothing formula not specified. Using: y ~ x
Smoothing formula not specified. Using: y ~ x
Smoothing formula not specified. Using: y ~ qss(x, lambda = 1)
Smoothing formula not specified. Using: y ~ qss(x, lambda = 0.1)
Smoothing formula not specified. Using: y ~ x
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