see 0.8.0
Major Changes
-
plot()
forperformance::check_model()
no longer produces a normal QQ plot
for GLMs. Instead, it now shows a half-normal QQ plot of the absolute value of
the standardized deviance residuals. -
plot()
forperformance::check_model()
and
performance::check_predictions()
gains atype
argument, to either create
density plots, or discrete dots resp. interval plots for posterior predictive
checks. -
plot()
forperformance::check_model()
gains ann_column
argument, to
define the number of columns for the diagnostic plots (by default, two
columns). -
plot()
forperformance::check_model()
sometimes failed to create the plot
under certain conditions, e.g. when the screen or app windows was zoomed-in.
If an error occurs, a much more informative error message is shown, providing
several possible solutions to resolve this problem. -
plot()
forparameters::equivalence_test()
now aligns the labelling with
theprint()
method. Hence, the legend title is no longer labelled"Decision on H0"
, but rather"Equivalence"
, to emphasize that we can assume practical
equivalence for effects, but that we cannot accept the H0 (in a frequentist
framework). -
Added some examples and cross references between docs. Furthermore, a vignette
about plotting functions for the datawizard package was added.
Bug fixes
-
Fixed issue with duplicated legend in the
plot()
method for
performance::check_predictions()
. -
Fixes issue in
plot.binned_residuals()
for models whose residuals were
completely inside error bounds. -
plot()
now works when using it on the output ofdescribe_distribution()
with aselect
argument of length 1.