Calculation for quantile-quantile plot.
Calculation for quantile-quantile plot.
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 )
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 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 |
distribution |
Distribution function to use, if x not specified |
dparams |
Additional parameters passed on to |
na.rm |
If |
show.legend |
logical. Should this layer be included in the legends?
|
inherit.aes |
If |
stat_qq
understands the following aesthetics (required aesthetics are in bold):
sample
x
y
sample quantiles
theoretical quantiles
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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