geom_*
and stat_*
for Producing Quantile Residual Q-Q Plots with `ggplot2`geom_qqrplot.Rd
Various geom_*
and stat_*
used within
autoplot
for producing quantile residual Q-Q plots.
geom_qqrplot(
mapping = NULL,
data = NULL,
stat = "identity",
position = "identity",
na.rm = FALSE,
show.legend = NA,
inherit.aes = TRUE,
...
)
stat_qqrplot_simint(
mapping = NULL,
data = NULL,
geom = "qqrplot_simint",
position = "identity",
na.rm = FALSE,
show.legend = NA,
inherit.aes = TRUE,
...
)
geom_qqrplot_simint(
mapping = NULL,
data = NULL,
stat = "qqrplot_simint",
position = "identity",
na.rm = FALSE,
show.legend = NA,
inherit.aes = TRUE,
...
)
stat_qqrplot_ref(
mapping = NULL,
data = NULL,
geom = "qqrplot_ref",
position = "identity",
na.rm = FALSE,
show.legend = NA,
inherit.aes = TRUE,
detrend = FALSE,
identity = TRUE,
probs = c(0.25, 0.75),
scale = c("normal", "uniform"),
...
)
geom_qqrplot_ref(
mapping = NULL,
data = NULL,
stat = "qqrplot_ref",
position = "identity",
na.rm = FALSE,
show.legend = NA,
inherit.aes = TRUE,
detrend = FALSE,
identity = TRUE,
probs = c(0.25, 0.75),
scale = c("normal", "uniform"),
...
)
geom_qqrplot_confint(
mapping = NULL,
data = NULL,
stat = "qqrplot_confint",
position = "identity",
na.rm = FALSE,
show.legend = NA,
inherit.aes = TRUE,
xlim = NULL,
n = 101,
detrend = FALSE,
type = c("pointwise", "simultaneous", "tail-sensitive"),
level = 0.95,
identity = TRUE,
probs = c(0.25, 0.75),
scale = c("normal", "uniform"),
style = c("polygon", "line"),
...
)
GeomQqrplotConfint
An object of class GeomQqrplotConfint
(inherits from Geom
, ggproto
, gg
) of length 6.
Set of aesthetic mappings created by 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.
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. A function
can be created
from a formula
(e.g. ~ head(.x, 10)
).
The statistical transformation to use on the data for this
layer, either as a ggproto
Geom
subclass or as a string naming the
stat stripped of the stat_
prefix (e.g. "count"
rather than
"stat_count"
)
Position adjustment, either as a string naming the adjustment
(e.g. "jitter"
to use 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.
If FALSE
, the default, missing values are removed with
a warning. If TRUE
, missing values are silently removed.
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.
It can also be a named logical vector to finely select the aesthetics to
display.
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()
.
Other arguments passed on to layer()
. These are
often aesthetics, used to set an aesthetic to a fixed value, like
colour = "red"
or size = 3
. They may also be parameters
to the paired geom/stat.
The geometric object to use to display the data, either as a
ggproto
Geom
subclass or as a string naming the geom stripped of the
geom_
prefix (e.g. "point"
rather than "geom_point"
)
logical, default FALSE
. If set to TRUE
the qqrplot is detrended,
i.e, plotted as a wormplot
.
logical. Should the identity line be plotted or a theoretical line
which passes through probs
quantiles on the "uniform"
or "normal"
scale.
numeric vector of length two, representing probabilities of reference line used.
character. Scale on which the quantile residuals will
be shown: "uniform"
(default) for uniform scale or "normal"
for normal scale.
Used for the reference line which goes through the first and third quartile
of theoretical distributions.
NULL
(default) or numeric. The x limits for computing the confidence intervals.
positive numeric. Number of points used to compute the confidence intervals, the more the smoother.
character. Should "pointwise"
(default), "simultaneous"
, or
"tail-sensitive"
confidence intervals of the (randomized) quantile residuals be visualized.
Simultaneous confidence intervals are based on the Kolmogorov-Smirnov test.
numeric. The confidence level required, defaults to 0.95
.
character. Style for plotting confidence intervals. Either "polygon"
(default)
or "line"
).
if (require("ggplot2")) {
## Fit model
data("CrabSatellites", package = "countreg")
m1_pois <- glm(satellites ~ width + color, data = CrabSatellites, family = poisson)
m2_pois <- glm(satellites ~ color, data = CrabSatellites, family = poisson)
## Compute qqrplot
q1 <- qqrplot(m1_pois, plot = FALSE)
q2 <- qqrplot(m2_pois, plot = FALSE)
d <- c(q1, q2)
## Get label names
xlab <- unique(attr(d, "xlab"))
ylab <- unique(attr(d, "ylab"))
main <- attr(d, "main")
main <- make.names(main, unique = TRUE)
d$group <- factor(d$group, labels = main)
## Polygon CI around identity line used as reference
gg1 <- ggplot(data = d, aes(x = expected, y = observed, na.rm = TRUE)) +
geom_qqrplot_ref() +
geom_qqrplot_confint(fill = "red") +
geom_qqrplot() +
geom_qqrplot_simint(
aes(
x = simint_expected,
ymin = simint_observed_lwr,
ymax = simint_observed_upr,
group = group
)
) +
xlab(xlab) + ylab(ylab)
gg1
gg1 + facet_wrap(~group)
## Polygon CI around robust reference line
gg2 <- ggplot(data = d, aes(x = expected, y = observed, na.rm = TRUE)) +
geom_qqrplot_ref(identity = FALSE, scale = attr(d, "scale")) +
geom_qqrplot_confint(identity = FALSE, scale = attr(d, "scale"), style = "line") +
geom_qqrplot() +
geom_qqrplot_simint(
aes(
x = simint_expected,
ymin = simint_observed_lwr,
ymax = simint_observed_upr,
group = group
)
) +
xlab(xlab) + ylab(ylab)
gg2
gg2 + facet_wrap(~group)
## Use different `scale`s with confidence intervals
q1 <- qqrplot(m1_pois, scale = "uniform", plot = FALSE)
q2 <- qqrplot(m2_pois, plot = FALSE)
gg3 <- ggplot(data = q1, aes(x = expected, y = observed, na.rm = TRUE)) +
geom_qqrplot_ref() +
geom_qqrplot_confint(fill = "red", scale = "uniform") +
geom_qqrplot()
gg3
gg4 <- ggplot(data = q2, aes(x = expected, y = observed, na.rm = TRUE)) +
geom_qqrplot_ref() +
geom_qqrplot_confint(fill = "red", scale = "uniform") +
geom_qqrplot()
gg4
}
#> Warning: Using the `size` aesthetic in this geom was deprecated in ggplot2 3.4.0.
#> ℹ Please use `linewidth` in the `default_aes` field and elsewhere instead.