data_plot()
extracts and transforms an object for plotting,
while plot()
visualizes results of functions from different packages in
easystats-project. See the documentation
for your object's class:
Arguments
- x
An object.
- data
The original data used to create this object. Can be a statistical model.
- ...
Arguments passed to or from other methods.
Details
data_plot()
is in most situation not needed when the purpose
is plotting, since most plot()
-functions in see internally call
data_plot()
to prepare the data for plotting.
Many plot()
-functions have a data
-argument that is needed when
the data or model for plotting can't be retrieved via data_plot()
. In
such cases, plot()
gives an error and asks for providing data or models.
Most plot()
-functions work out-of-the-box, i.e. you don't need to do much
more than calling plot(<object>)
(see 'Examples'). Some plot-functions
allow to specify arguments to modify the transparency or color of geoms,
these are shown in the 'Usage' section.
Examples
if (FALSE) {
library(bayestestR)
if (require("rstanarm")) {
model <- stan_glm(
Sepal.Length ~ Petal.Width * Species,
data = iris,
chains = 2, iter = 200, refresh = 0
)
x <- rope(model)
plot(x)
x <- hdi(model)
plot(x) + theme_modern()
data <- rnorm(1000, 1)
x <- p_direction(data)
plot(x)
x <- p_direction(model)
plot(x)
model <- stan_glm(
mpg ~ wt + gear + cyl + disp,
chains = 2,
iter = 200,
refresh = 0,
data = mtcars
)
x <- equivalence_test(model)
plot(x)
}
}