Calculation for quantile-quantile plot.

Usage

stat_qq(mapping = NULL, data = NULL, geom = "point", position = "identity", distribution = qnorm, 
  dparams = list(), na.rm = FALSE, ...)

Arguments

distribution
Distribution function to use, if x not specified
dparams
Parameters for distribution function
...
Other arguments passed to distribution function
na.rm
If FALSE (the default), removes missing values with a warning. If TRUE silently removes missing values.
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.
geom
The geometric object to use display the data
position
The position adjustment to use for overlappling points on this layer

Value

a data.frame with additional columns: samplesample quantiles theoreticaltheoretical quantiles

Description

Calculation for quantile-quantile plot.

Aesthetics

stat_qq understands the following aesthetics (required aesthetics are in bold):

  • sample
  • x
  • y

Examples

# From ?qqplot y <- rt(200, df = 5) qplot(sample = y, stat="qq")

# qplot is smart enough to use stat_qq if you use sample qplot(sample = y)

qplot(sample = precip)

qplot(sample = y, dist = qt, dparams = list(df = 5))

df <- data.frame(y) ggplot(df, aes(sample = y)) + stat_qq()

ggplot(df, aes(sample = y)) + geom_point(stat = "qq")

# Use fitdistr from MASS to estimate distribution params library(MASS) params <- as.list(fitdistr(y, "t")$estimate)
Warning message: NaNs produced Warning message: NaNs produced
ggplot(df, aes(sample = y)) + stat_qq(dist = qt, dparam = params)

# Using to explore the distribution of a variable qplot(sample = mpg, data = mtcars)

qplot(sample = mpg, data = mtcars, colour = factor(cyl))