stat_qq_point {qqplotr} | R Documentation |
Quantile-quantile points
Description
Draws quantile-quantile points, with an additional detrend option.
Usage
stat_qq_point(
mapping = NULL,
data = NULL,
geom = "point",
position = "identity",
na.rm = TRUE,
show.legend = NA,
inherit.aes = TRUE,
distribution = "norm",
dparams = list(),
detrend = FALSE,
identity = FALSE,
qtype = 7,
qprobs = c(0.25, 0.75),
down.sample = NULL,
...
)
Arguments
mapping |
Set of aesthetic mappings created by |
data |
The data to be displayed in this layer. There are three options: If A A |
geom |
The geometric object to use to display the data, either as a
|
position |
Position adjustment, either as a string naming the adjustment
(e.g. |
na.rm |
If |
show.legend |
logical. Should this layer be included in the legends?
|
inherit.aes |
If |
distribution |
Character. Theoretical probability distribution function
to use. Do not provide the full distribution function name (e.g.,
|
dparams |
List of additional parameters passed on to the previously
chosen |
detrend |
Logical. Should the plot objects be detrended? If |
identity |
Logical. Only used if |
qtype |
Integer between 1 and 9. Only used if |
qprobs |
Numeric vector of length two. Only used if |
down.sample |
Integer specifying how many points you want to sample
in a reduced sample (i.e., a down sample). The default value is |
... |
Other arguments passed on to |
References
Thode, H. (2002), Testing for Normality. CRC Press, 1st Ed.
Examples
# generate random Normal data
set.seed(0)
smp <- data.frame(norm = rnorm(100))
# Normal Q-Q plot of simulated Normal data
gg <- ggplot(data = smp, mapping = aes(sample = norm)) +
stat_qq_point() +
labs(x = "Theoretical Quantiles", y = "Sample Quantiles")
gg
# Exponential Q-Q plot of mean ozone levels (airquality dataset)
di <- "exp"
dp <- list(rate = 1)
gg <- ggplot(data = airquality, mapping = aes(sample = Ozone)) +
stat_qq_point(distribution = di, dparams = dp) +
labs(x = "Theoretical Quantiles", y = "Sample Quantiles")
gg