ggplot2 (version 1.0.0)

stat_qq: Calculation for quantile-quantile plot.

Description

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:
• sample
  sample quantiles
• theoretical
  theoretical quantiles

Aesthetics

[results=rd,stage=build]{ggplot2:::rd_aesthetics("stat", "qq")} # 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) 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))