1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189
|
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/stat-qq-line.R, R/stat-qq.r
\name{geom_qq_line}
\alias{geom_qq_line}
\alias{stat_qq_line}
\alias{geom_qq}
\alias{stat_qq}
\title{A quantile-quantile plot}
\usage{
geom_qq_line(
mapping = NULL,
data = NULL,
geom = "path",
position = "identity",
...,
distribution = stats::qnorm,
dparams = list(),
line.p = c(0.25, 0.75),
fullrange = FALSE,
na.rm = FALSE,
show.legend = NA,
inherit.aes = TRUE
)
stat_qq_line(
mapping = NULL,
data = NULL,
geom = "path",
position = "identity",
...,
distribution = stats::qnorm,
dparams = list(),
line.p = c(0.25, 0.75),
fullrange = FALSE,
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
)
stat_qq(
mapping = NULL,
data = NULL,
geom = "point",
position = "identity",
...,
distribution = stats::qnorm,
dparams = list(),
na.rm = FALSE,
show.legend = NA,
inherit.aes = TRUE
)
}
\arguments{
\item{mapping}{Set of aesthetic mappings created by \code{\link[=aes]{aes()}}. If specified and
\code{inherit.aes = TRUE} (the default), it is combined with the default mapping
at the top level of the plot. You must supply \code{mapping} if there is no plot
mapping.}
\item{data}{The data to be displayed in this layer. There are three
options:
If \code{NULL}, the default, the data is inherited from the plot
data as specified in the call to \code{\link[=ggplot]{ggplot()}}.
A \code{data.frame}, or other object, will override the plot
data. All objects will be fortified to produce a data frame. See
\code{\link[=fortify]{fortify()}} for which variables will be created.
A \code{function} will be called with a single argument,
the plot data. The return value must be a \code{data.frame}, and
will be used as the layer data. A \code{function} can be created
from a \code{formula} (e.g. \code{~ head(.x, 10)}).}
\item{geom}{The geometric object to use to display the data, either as a
\code{ggproto} \code{Geom} subclass or as a string naming the geom stripped of the
\code{geom_} prefix (e.g. \code{"point"} rather than \code{"geom_point"})}
\item{position}{Position adjustment, either as a string naming the adjustment
(e.g. \code{"jitter"} to use \code{position_jitter}), or the result of a call to a
position adjustment function. Use the latter if you need to change the
settings of the adjustment.}
\item{...}{Other arguments passed on to \code{\link[=layer]{layer()}}. These are
often aesthetics, used to set an aesthetic to a fixed value, like
\code{colour = "red"} or \code{size = 3}. They may also be parameters
to the paired geom/stat.}
\item{distribution}{Distribution function to use, if x not specified}
\item{dparams}{Additional parameters passed on to \code{distribution}
function.}
\item{line.p}{Vector of quantiles to use when fitting the Q-Q line, defaults
defaults to \code{c(.25, .75)}.}
\item{fullrange}{Should the q-q line span the full range of the plot, or just
the data}
\item{na.rm}{If \code{FALSE}, the default, missing values are removed with
a warning. If \code{TRUE}, missing values are silently removed.}
\item{show.legend}{logical. Should this layer be included in the legends?
\code{NA}, the default, includes if any aesthetics are mapped.
\code{FALSE} never includes, and \code{TRUE} always includes.
It can also be a named logical vector to finely select the aesthetics to
display.}
\item{inherit.aes}{If \code{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. \code{\link[=borders]{borders()}}.}
}
\description{
\code{geom_qq()} and \code{stat_qq()} produce quantile-quantile plots. \code{geom_qq_line()} and
\code{stat_qq_line()} compute the slope and intercept of the line connecting the
points at specified quartiles of the theoretical and sample distributions.
}
\section{Aesthetics}{
\code{stat_qq()} understands the following aesthetics (required aesthetics are in bold):
\itemize{
\item \strong{\code{sample}}
\item \code{group}
\item \code{x}
\item \code{y}
}
Learn more about setting these aesthetics in \code{vignette("ggplot2-specs")}.
\code{stat_qq_line()} understands the following aesthetics (required aesthetics are in bold):
\itemize{
\item \strong{\code{sample}}
\item \code{group}
\item \code{x}
\item \code{y}
}
Learn more about setting these aesthetics in \code{vignette("ggplot2-specs")}.
}
\section{Computed variables}{
These are calculated by the 'stat' part of layers and can be accessed with \link[=aes_eval]{delayed evaluation}. \cr Variables computed by \code{stat_qq()}:
\itemize{
\item \code{after_stat(sample)}\cr Sample quantiles.
\item \code{after_stat(theoretical)}\cr Theoretical quantiles.
}
Variables computed by \code{stat_qq_line()}:
\itemize{
\item \code{after_stat(x)}\cr x-coordinates of the endpoints of the line segment connecting the points at the chosen quantiles of the theoretical and the sample distributions.
\item \code{after_stat(y)}\cr y-coordinates of the endpoints.
}
}
\examples{
\donttest{
df <- data.frame(y = rt(200, df = 5))
p <- ggplot(df, aes(sample = y))
p + stat_qq() + stat_qq_line()
# 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"]) +
stat_qq_line(distribution = qt, dparams = params["df"])
# Using to explore the distribution of a variable
ggplot(mtcars, aes(sample = mpg)) +
stat_qq() +
stat_qq_line()
ggplot(mtcars, aes(sample = mpg, colour = factor(cyl))) +
stat_qq() +
stat_qq_line()
}
}
|