data_plot | R Documentation |
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:
bayestestR::bayesfactor_models()
bayestestR::bayesfactor_parameters()
bayestestR::equivalence_test()
bayestestR::estimate_density()
bayestestR::hdi()
bayestestR::p_direction()
bayestestR::p_significance()
bayestestR::si()
effectsize::effectsize()
modelbased::estimate_contrasts()
parameters::compare_parameters()
parameters::describe_distribution()
parameters::model_parameters()
parameters::principal_components()
parameters::n_clusters()
parameters::n_factors()
parameters::simulate_parameters()
performance::check_collinearity()
performance::check_heteroscedasticity()
performance::check_homogeneity()
performance::check_normality()
performance::check_outliers()
performance::compare_performance()
performance::performance_roc()
performance::check_predictions()
data_plot(x, ...)
## S3 method for class 'compare_performance'
data_plot(x, data = NULL, ...)
x |
An object. |
... |
Arguments passed to or from other methods. |
data |
The original data used to create this object. Can be a statistical model. |
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.
library(bayestestR)
library(rstanarm)
model <<- suppressWarnings(stan_glm(
Sepal.Length ~ Petal.Width * Species,
data = iris,
chains = 2, iter = 200, refresh = 0
))
x <- rope(model, verbose = FALSE)
plot(x)
x <- hdi(model)
plot(x) + theme_modern()
x <- p_direction(model, verbose = FALSE)
plot(x)
model <<- suppressWarnings(stan_glm(
mpg ~ wt + gear + cyl + disp,
chains = 2,
iter = 200,
refresh = 0,
data = mtcars
))
x <- equivalence_test(model, verbose = FALSE)
plot(x)
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