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 = stats::qnorm, dparams = list(), na.rm = FALSE, show.legend = NA, inherit.aes = TRUE)
 geom_qq(mapping = NULL, data = NULL, geom = "point", position = "identity", ..., distribution = stats::qnorm, dparams = list(), na.rm = FALSE, show.legend = NA, inherit.aes = TRUE)

Arguments

mapping

Set of aesthetic mappings created by aes or aes_. If specified and inherit.aes = TRUE (the default), it is combined with the default mapping at the top level of the plot. You must supply mapping if there is no plot mapping.

data

The data to be displayed in this layer. There are three options:

If NULL, the default, the data is inherited from the plot data as specified in the call to ggplot.

A data.frame, or other object, will override the plot data. All objects will be fortified to produce a data frame. See fortify for which variables will be created.

A function will be called with a single argument, the plot data. The return value must be a data.frame., and will be used as the layer data.

geom

The geometric object to use display the data

position

Position adjustment, either as a string, or the result of a call to a position adjustment function.

...

other arguments passed on to layer. These are often aesthetics, used to set an aesthetic to a fixed value, like color = "red" or size = 3. They may also be parameters to the paired geom/stat.

distribution

Distribution function to use, if x not specified

dparams

Additional parameters passed on to distribution function.

na.rm

If FALSE (the default), removes missing values with a warning. If TRUE silently removes missing values.

show.legend

logical. Should this layer be included in the legends? NA, the default, includes if any aesthetics are mapped. FALSE never includes, and TRUE always includes.

inherit.aes

If FALSE, overrides the default aesthetics, rather than combining with them. This is most useful for helper functions that define both data and aesthetics and shouldn't inherit behaviour from the default plot specification, e.g. borders.

Aesthetics

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

sample
x
y

Computed variables

sample: sample quantiles
theoretical: theoretical quantiles

Examples

Run this code

 df <- data.frame(y = rt(200, df = 5)) p <- ggplot(df, aes(sample = y)) p + stat_qq() p + geom_point(stat = "qq")  # Use fitdistr from MASS to estimate distribution params params <- as.list(MASS::fitdistr(df$y, "t")$estimate) ggplot(df, aes(sample = y)) +  stat_qq(distribution = qt, dparams = params["df"])  # Using to explore the distribution of a variable ggplot(mtcars) +  stat_qq(aes(sample = mpg)) ggplot(mtcars) +  stat_qq(aes(sample = mpg, colour = factor(cyl)))

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