Changelog

Source: NEWS.md

see 0.15.0

CRAN release: 2026-10-16

Changes

• The Linearity and Homogeneity of Variance panels of check_model() (and the plot of check_heteroscedasticity()) now draw the mean of each cell, joined by a line, in place of the LOESS smoother when the fitted values take only a few distinct values, for example in models with only categorical predictors. A LOESS fit over so few values warned and could bend far outside the data. When show_ci is TRUE, the cell means get 95% error bars. Note that performance currently turns show_ci off for models whose terms are all factors without interactions (#464).

• plot() for check_model() and check_heteroscedasticity() gains a show_smooth argument. With show_smooth = FALSE, the Linearity and Homogeneity of Variance panels draw neither the LOESS smoother nor the cell means, the Influential Observations panel draws no LOESS smoother, and the subtitles of the Linearity and Homogeneity of Variance panels no longer refer to a reference line (#464).

• plot() for datawizard::means_by_group() gets a flip argument. Use flip = FALSE to show the groups on the horizontal axis (#455).

• geom_violinhalf() and geom_violindot() are now drawn with the ggdist package (ggdist::stat_slab() and ggdist::geom_dots()), which they now need (version 3.3.3 or later). They work with facets and free scales (#81, #385), and the plots look a little different. Dodged groups each take half of their dodge cell, from its centre, as before. The dots of geom_violindot() were not dodged before. By default, they now go in the other half of the cell (they overlap a flipped half violin). The new interval argument adds the median with 66% and 95% intervals (#68). The binwidth default of geom_violindot() is now NA (it was 0.05), so ggdist sizes the dots to the data (#44). Other arguments in ... of geom_violindot() now go to ggdist::geom_dots() (instead of geom_dotplot()) as well as to the half violins, except the arguments of the density, the layout, and the interval, which go to the half violins only (see ?geom_violindot). A width in ... is the width of a whole violin, as in geom_violin(), so each half violin is half as wide. bounds must contain all values; otherwise the half violins are not drawn. The stat argument is now ignored, with a warning for any value other than "ydensity" or ggplot2::StatYdensity. geom_violindot() no longer works with coord_polar().

• plot() for modelbased::estimate_contrasts() now draws joint contrasts of two or more variables, such as contrast = c("am", "cyl"). The x axis shows the combinations of levels, such as “auto, 4”.

• plot() for modelbased::estimate_contrasts() gains a show_data argument. With show_data = TRUE, the plot draws the raw data of the model as jittered points behind the lighthouses (easystats/modelbased#114).

• plot() for modelbased::estimate_contrasts() now draws more kinds of estimates. It draws means in a Probability, Proportion, or Rate column, such as the probabilities of a logistic model. It draws ratio contrasts from comparison = ratio ~ pairwise as ratios of the means. With the default backend, it draws contrasts of a log response estimated with transform = TRUE as ratios of the back-transformed means. The plot stops with an error for contrasts back-transformed from some other transformations, such as sqrt(y). When insight::find_transformation() reports a transformation other than "identity", it also stops for ratio contrasts estimated with transform = TRUE. It also stops for contrasts and means on different scales, as their predict or transform arguments show. The help page lists the exceptions. With show_data = TRUE, the plot draws a logical or two-level factor response as 0 and 1. It also draws the raw data of y for a response log(y), log2(y), or log10(y). This needs contrasts and means estimated with transform = TRUE.

• plot() for modelbased::estimate_contrasts() now draws ordinal and multinomial models, such as MASS::polr() and mclogit::mblogit(), with one panel per response category. Each panel shows the probabilities of that category and the contrasts within it. Contrasts between two categories are not drawn. show_data = TRUE stops with an error for these models. The plot also draws Bayesian ratio contrasts from comparison = ratio ~ pairwise as ratios. When insight::find_transformation() reports "identity", it draws ratio contrasts estimated with transform = TRUE as ratios. It accepts contrasts and means on the link scale from the marginaleffects and emmeans backends together. For some models, such as lm(y ~ x), the link scale counts as the response scale. These models have an identity link, and insight::find_transformation() reports their response as "identity". The link scale does not count for a model with a zero-inflation or hurdle part.

• plot() for modelbased::estimate_contrasts() now shows only the panels of the by levels that the contrasts have. It leaves out the means and raw data of other levels. A numeric contrast variable at unevenly spaced values, such as contrast = "wt=c(2,2.5,4)", gets a continuous x axis that keeps their spacing. Joint contrasts of three or more variables show one level per line in the axis labels. A by variable named PANEL, ROW, COL, SCALE_X, or SCALE_Y no longer stops the plot.

• If a term with a VIF below 2 has an upper confidence limit that is infinite or above the top of the plot, the collinearity plot now has a caption. The caption says that the interval formula (from performance) fails near VIF = 1, and that this is not high collinearity. This applies to plot() for check_collinearity() and to the collinearity panel of check_model(). The y axis now extends below VIF = 1, so the axis no longer cuts off points at 1 (#399).

Bug fixes

• plot() for structural equation models from parameters::model_parameters() drew latent factors as observed variables and indicators as latent variables. Latent factors are now drawn as circles and indicators as squares.

• plot() for structural equation models now gives an informative error when the selected component has no paths to plot, for example component = "regression" for a confirmatory factor analysis (#243).

• geom_binomdensity() now works with facets. It no longer drops the columns other than x and y, so each panel shows only its own data (#192).

• When check_model() failed to create plots, the informative message about troubleshooting and workarounds was no longer printed. This should now work again.

• plot() for modelbased::estimate_contrasts() now draws each contrast estimated with by from the means of its own by level. Previously, it mixed the means of all by levels into each contrast. If the means listed the by variable first, it drew no contrasts. The plot now shows one panel per level, or combination of levels, of the by variables. The x axis now shows the contrasted variable in the order of its levels (easystats/modelbased#267).

• When some observations had a missing Cook’s distance, plot() for check_outliers() failed with “arguments imply differing number of rows”. An example is rows with missing values in a model fitted with na.action = na.exclude. The scree and count plots now leave these observations out, and the labels still name the right rows.

see 0.14.2

CRAN release: 2026-09-01

Changes

• Argument linewidth was renamed to size_line, to be consistent across the easystats-ecosystem. However, linewidth remains as an alias, since this is the name of the corresponding ggplot2-argument.

• plot() for check_heteroscedasticity() now works for GLM’s and models from package glmmTMB. Previously, check_heteroscedasticity() worked for linear models only.

Bug fixes

• plot() for check_heteroscedasticity() now uses Pearson residuals for glmmTMB and MixMod models. Previously these residuals were divided by a single scalar, which is only correct when the variance function does not depend on the mean; for non-mixed binomial and Poisson models that scalar was 1, so the plot could suggest heteroscedasticity for correctly specified models. See easystats/performance#926.

see 0.14.1

CRAN release: 2026-06-29

Changes

• Added plot method for prior predictive checks, from the performance::check_priors() function.

• The plot() method for performance::check_dag() gains a size_arrow argument, to control the size of arrows in the DAG.

• Added plot method for datawizard::means_by_groups() objects.

Bug fixes

• The type argument in performance::check_predictions() was not recognized in the plot() method.

• plot() for model_parameters() with lavaan objects did not work when the object contained no loadings component.

see 0.14.0

CRAN release: 2026-05-24

Changes

• plot() for parameters::factor_analysis() and parameters::principal_components() gains a new type option, "graph". This creates a graph with nodes/edges indicating factor loadings.

• Updated plot-method for performance::check_model() for Bayesian ordinal models.

• New geom_point_halo(), geom_pointrange_halo(), geom_jitter_halo() and geom_count_halo() geoms, which add a slight contour around the points

• Outlier plots no longer show extreme smoother curves for models with a small number of observations or a small number of outlier data points.

Bug fixes

• Fixed the *_borderless aliases for geom_point2() or geom_jitter2(), which were broken and did not render as intended.

see 0.13.0

CRAN release: 2026-01-30

Breaking Changes

• Data points in plot() for objects from parameters::model_parameters() were sorted in reverse order when using the sort argument. This was fixed, thus, sort = "ascending" now sorts the data in ascending order in plot/math logic.

Major Changes

• Daniel Lüdecke is now the main maintainer of the package.

• Several plot() methods gain a theme argument, to control the visual themes for plots. This is in particular useful for plots that consist of several single plots, like the one returned by check_model().

Changes

• plot() for check_model() now limits the number of data points for models with many observations, to reduce the time for rendering the plot. Use argument maximum_dots to define the maximum number of data points to show.

• plot() for check_model() extracts the show_ci attribute from objects returned by check_model(), to show or hide confidence intervals.

Bug fixes

• Fixed issue in the plot() method for estimate_density() with vector input and group_by argument.

see 0.12.0

CRAN release: 2025-09-14

Major Changes

• The minimum needed R version has been bumped to 4.1, since correlation, a runtime dependency, requires it.

Changes

• plot() for performance::check_normality() now also supports objects from psych::fa(), psych::principal() and parameters::factor_analysis().

• plot() for performance::check_outliers() gets a new "scree" type option, to create a scree plot of outlier statistics.

• Minor re-labelling of axis titles and subtitles in plot() for performance::check_residuals().

• Updates the package to adapt to the changes in the latest ggplot2 release.

• Themes get an axis.text.space argument, to define the spacing between axis lines and axis labels. Due to changes in ggplot2, the default spacing was slightly changed, now it can be set to the desired value using this argument.

see 0.11.0

CRAN release: 2025-03-11

Changes

• All theme_*() function get a ... argument that is passed to ggplot2::theme().

• Arguments that change the size of elements in theme_*() functions (like plot.title.size or axis.text.size now scale with the base_size argument, to ensure proper scaling of plots when the base-size is changed.

• Added a new theme, theme_azurelight(), with a light-blue character, and reduced use of grid lines.

• theme_modern() now recognizes a show.ticks argument, to add tick marks to the plot and slightly increase the distance between axis labels and the related axis.

• Color scale functions (those starting with scale_*()) get a new "gradient" palette, which are simply the color values for blue and orange colors from that palette. Furthermore, color scale functions now automatically select an appropriate palette (usually, "contrast" or "gradient") depending on whether discrete or continuous color scales are requested.

Bug fixes

• Fixed issue with adding prior layers to plots from estimate_density().

see 0.10.0

CRAN release: 2025-01-22

Changes

• plot() for p_function() now checks the values of the size_length argument, to give an informative error message when the input is not valid.

• plot() for model_parameters() now also plots group-levels of random effects (i.e. for mixed models, when model_parameters(x, ..., group_level = TRUE)).

• plot() for model_parameters() gets a show_direction argument, to turn off the direction of the effect in the plot.

• plot() for model_parameters() now gives an informative error message when trying to plot Anova tables (which does not work).

• plot() for simulate_parameters() now better copes with models that have multiple response levels (e.g. multinomial models).

• Gains patchwork as a hard dependency given its importance for the package.

Bug fixes

• Fixed issue in plot() for bayestestR::si().

• Fixed issue in plot() for parameters::model_parameters() for GAM models.

see 0.9.0

CRAN release: 2024-09-06

Changes

• New plot() method for performance::check_dag().

• Minor improvements to plot() for methods p_direction() and p_significance(), which also support forthcoming changes in the parameters package.

Bug fixes

• Fixed issue in plot() for performance::check_model() when package qqplotr is not installed.

see 0.8.5

CRAN release: 2024-07-17

Major Changes

• The minimum needed R version has been bumped to 4.0.

Minor Changes

• Improved scaling for detrended QQ plots when package qqplotr is not installed. The normal and the detrended QQ plots are now visually more similar.

• Gets rid of warnings due to API changes in the datawizard package.

Bug fixes

• Fixed CRAN test failures.

see 0.8.4

CRAN release: 2024-04-29

Minor Changes

• Fixes warnings generated from the ggplot2 3.5.0 release.

• Small adjustment to size of point geoms for check_model() plots.

• More arguments to change base font sizes and geom sizes are now passed to downstream plot-functions (i.e., plot() for check_model() passes arguments to change geom sizes to the underlying plot-functions).

• plot() for check_predictions() now supports Bayesian regression models from brms and rstanarm.

Bug fixes

• Corrected order of models for plot.compare_parameters().

see 0.8.3

CRAN release: 2024-03-24

Major changes

• New plot() method for simulated residuals (implemented in the performance package).

• plot() for check_model() was revised and now includes more accurate Q-Q plots for non-Gaussian models.

Minor Changes

• plot.check_model() now passes arguments size_point and size_line to the posterior predictive check plot.

• Minor changes regarding the latest update of ggplot2.

see 0.8.2

CRAN release: 2024-02-14

Minor Changes

• plot.n_factors() now shows a dashed line over the bars, indicating the cumulate explained variance by the number of factors.

• plot.check_outliers() now dodges the x-axis labels, to avoid overlapping labels.

see 0.8.1

CRAN release: 2023-11-03

Major Changes

• This release changes the licensing model of see to an MIT license.

New features

• There is now a plot() method for outputs of datawizard::data_tabulate() (#293).

Minor Changes

• The print() method for performance::check_model() now also evaluates the default plot type for posterior predictive checks.

• QQ/PP-plots now default to drawing simultaneous testing bands (when the qqplotr package is available). Previous behavior can be restored by setting method = "pointwise".

• Plot method for performance::check_normality() now default to a detrended QQ-plot. Previous behavior can be restored by setting type = "density".

• Plot method for binned_residuals() gains a show_smooth argument, to show or hide the smooth line.

• Plot method for check_predictions() gains a x_limits argument, to limit the x-axis-range. This can be useful to “zoom in” certain parts of the plot.

see 0.8.0

CRAN release: 2023-06-05

Major Changes

• plot() for performance::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() for performance::check_model() and performance::check_predictions() gains a type argument, to either create density plots, or discrete dots resp. interval plots for posterior predictive checks.

• plot() for performance::check_model() gains an n_column argument, to define the number of columns for the diagnostic plots (by default, two columns).

• plot() for performance::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() for parameters::equivalence_test() now aligns the labelling with the print() 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 of describe_distribution() with a select argument of length 1.

see 0.7.5

CRAN release: 2023-03-23

Changes

• Changed the default “yellow” color in palette_okabeito() to "#F5C710" instead of "#F0E442" to increase visibility against a white background. For the original Okabe-Ito palette, set palette = "full_original" or palette = "black_first_original".

• Deals with deprecated arguments and functions in recent ggplot2 updates.

see 0.7.4

CRAN release: 2022-11-25

Changes

• Updates docs and tests for ggplot2 release (3.4.0).

• New function scale_color_colorhex() provides color scales based on palettes from color-hex.com (#245).

• The default for the smoothing bandwidth from plot.check_predictions() has changed from "nrd0" to "nrd", which seems to produce better fitting plots for non-Gaussian models. Furthermore, performance::check_predictions() accepts a bw argument (smoothing bandwidth), which is passed down to the plot() method’s density-estimation.

Bug fixes

• Fixed issues with plot() for check_outliers() for models with convergence issues.

see 0.7.3

CRAN release: 2022-09-20

Changes

• Indrajeet Patil is now the maintainer.

• The minimum needed R version has been bumped to 3.6.

• Replaced deprecated arguments in function calls.

Bug fixes

• Fixed issues in the plot() method from model_parameters() for intercept-only models.

see 0.7.2

CRAN release: 2022-08-10

Changes

• Added aesthetics argument to all color and fill scale functions so that the same scale can be applied to multiple aesthetics and so that the functions can be used with other aesthetics from other packages (e.g., edge_color).

• Added Okabe-Ito color palette (palette_okabeito, scale_color_okabeito()) etc.)

• Several minor improvements.

Bug fixes

• Fixed CRAN check issues.

see 0.7.1

CRAN release: 2022-06-20

Changes

• Changed style for plot.check_collinearity(), which is now a dot-plot, including error bars.

Bug fixes

• plot.check_model() did not apply the colors argument to all sub-plots.

• plot() for model_parameters() could fail when model objects’ class attribute had more than one element.

see 0.7.0

CRAN release: 2022-03-31

• Improved plotting for performance::check_model():

  • using more appropriate plots for binomial models

  • the redundant density-plot of normality-checks was replaced by the posterior predictive check plot.

  • includes a plot to investigate overdispersion for count-models.

• Minor improvements for some plot-methods (colour tweaking, labelling, …).

see 0.6.9

CRAN release: 2022-02-15

• Minor changes to catch up with changes from other easystats-packages.

see 0.6.8

CRAN release: 2021-10-03

New features

• Add option to show density layers for Bayesian and bootstrapped models in plot() for parameters::model_parameters().

• Negative coefficients in plot() for parameters::model_parameters() are now always red.

• Improve support for parameters::model_parameters() from emmeans objects.

• Updated code and examples to work with new API decisions made for the performance package.

Bug fixes

• Fix density plots for frequentist models.

see 0.6.5

General

• check_model() function now uses patchwork instead of gridExtra to arrange plots in a grid.

• Reduced/removed some package dependencies.

• Revise plot() for bayestestR::bayesfactor() to meet forthcoming changes in the bayestestR package.

New features

• New functions geom_from_list and geoms_from_list to create geoms from lists.

• Plotting for normality check is now supported for afex_aov models.

Bug fixes

• Fixed issue that argument show_intercept is no longer ignored in plot() for rope().

see 0.6.3

CRAN release: 2021-04-09

New plot functions

• Added plot-function for parameters::compare_parameters().

• Added option to detrend QQ/PP plots.

changes

• Plot for SEM models now has arrows pointing from the latent variables towards the manifest variables.

• The plot() method for check_model() was revised and should now be more consistent regarding titles and subtitles, as well as color schemes and plot order. Furthermore, the plot for influential observation was changed in order to better catch the potential influential observations.

• The check_heteroscedasticity() plot contains a dashed horizontal line, which makes it to assess the homoscedasticity assumption.

• The y-axis label for check_collinearity() plot clarifies that the measure being plotted is VIF. This was unclear when this plot was embedded in a grid of plots from check_model() containing multiple checks.

• Plotting methods for performance_roc() and performance_accuracy() show correct labels now.

Bug fixes

• Fixed issue with wrong labelling of CI-levels for plot.see_hdi().

• Fixed minor issues due to breaking changes in other easystats-packages.

see 0.6.2

CRAN release: 2021-02-04

Changes to functions

• plot() for performance::check_normality() gains a alpha-argument, to change the alpha-level of confidence bands.

• The ... argument for geom_violindot() is now also passed to to geom_violinhalf(), allowing, e.g., to change the alpha value of the violin-geoms as well.

• Reorganized order of arguments in geom_violindot(), so aesthetics arguments like fill are not absorbed by partial matching for arguments like fill_dots.

Bug fixes

• plot() for performance::check_normality() shows more accurate QQ-plots.

• plot() for performance::check_normality() show correct confidence bands for QQ- and PP-plots (with qqplotr). Previous bands were extremely narrow!

see 0.6.1

CRAN release: 2020-12-06

Changes to functions

• plot() for parameters::model_parameters() now supports models from package metaBMA

• plot() for parameters::model_parameters() gains a weight_points argument, to adjust the point-size depending on study-weights for meta-analysis models.

• plot() for parameters::model_parameters() now labels the x-axis depending on model-type (i.e. “Odds Ratio” instead of “Exp(Estimate)”) when this information is available.

Bug fixes

• Minor fix in plot() for parameters::model_parameters() for brmsfit models.

see 0.6.0

CRAN release: 2020-09-13

Breaking changes

• Harmonized spelling of arguments. Formerly, we had text_size and size_text, or just size even if only in the context of text labels. We now tried to harmonize these kind of arguments to gain more consistency throughout the different plot() methods.

New plot functions

• Added plot-function for parameters::model_parameters() for brms-meta-analysis models.

• Added plot-function for performance::pp_check().

Changes to functions

• plot() for parameters::model_parameters() gains a size_text-argument, to add text values for estimates and confidence intervals to the plot (see also vignette).

• plot() for parameters::model_parameters() from meta-analysis models (e.g. from metafor) gains a type argument, to create funnel plots with type = "funnel".

• plot() for bayestestR::estimate_density() and parameters::simulate_parameters() were revised, and now also include the point-estimate and error bar. Therefore, arguments centrality and ci were added.

Bug fixes

• Fixed bug in plot.model_parameters() when standardize was "basic", "smart" or "posthoc".

• Fixed wrong axis labelling for ROC-curves (from performance::performance_roc()).

see 0.5.2

CRAN release: 2020-07-27

Changes to functions

• plot() for correlation::correlation() gains a type and size argument, to plot correlation matrices either as tiles or circles.

Color Scales and Palettes

• Added new color-palettes.

• Palettes for existing color scales have been revamped.

• Added "light" palettes for dark themes.

see 0.5.1

CRAN release: 2020-06-13

Changes to functions

• Plot-function for parameters::describe_distribution() gains highlight, highlight_color and size arguments.

• Plot-function for parameters::describe_distribution() now uses thin bars for variables with integer values (instead of less precise histogram).

• Plot-function for performance::check_normality() gains size and point_size arguments.

• Plot-function for performance::check_normality() now also plots normality of random effects, when check_normality(effects = "random") was called.

• Legend labels nopw show a percentage-sign where applicable (for instance, for plot.hdi()).

Bug fixes

• Fixed issue with argument n_column in plot.p_significant(), plot.hdi(), and plot.p_direction(), which stopped working since R 4.0.0.

• Fixed issue in plot.performance_roc() with swapped x/y axes.

see 0.5.0

CRAN release: 2020-04-25

New functions

• golden_ratio() was added as a helper to get nice proportions.

New plot functions

• Added plot-function for correlation::summary().

• Added plot-function for parameters::describe_distribution().

• Added plot-function for effectsize::equivalence_test().

• Added plot-function for various effectsize-functions, like effectsize::eta_squared().

Changes to functions

• plot.estimate_density() now also works for density estimation of data frames.

• plot.equivalence_test() now also works for frequentist models and data frames (see parameters::equivalence_test()).

• Slightly changed plotting-style for plot.equivalence_test().

see 0.4.1

CRAN release: 2020-03-06

General

• Reduce package dependencies.

New plot-functions

• Added plot-function for correlation::correlation().

Changes to functions

• plot() for model_parameters.rma() now arranges facets by subgroups (see vignettes).

• minor improvements to plot() for parameters::cluster_analysis().

• minor improvements to plot() for parameters::model_parameters.brmsfit().

• Plot-function for bayestestR::si() gets a support_only argument, to plot only the support data or the “raw” prior and posterior distributions.

see 0.4.0

CRAN release: 2020-01-15

Breaking changes

• Arguments ncol and nrow in plots() were renamed into n_columns and n_rows to be consistent with arguments from other functions in the see-package.

New plot-functions

• Added plot-function for performance::compare_performance().

• Added plot-function for bayestestR::si().

Changes to functions

• plot()-functions for the bayestestR-package now also support BFBayesFactor and MCMCglmm objects.

• plot() for parameters::model_parameters() now uses fixed axis for facets when model is an ordinal or cumulative link model (because all facets are on the same scale, and thus parameters are easier to compare).

Bug fixes

• Fixed issue with group coloring for parameters::model_parameters() when exponentiate = TRUE.

• Fixes issue with plot.point_estimate() for vectors.

see 0.3.0

CRAN release: 2019-11-19

Breaking changes

• how_to_plot() was removed for the time being, due to its inadequate maintenance effort. It might be re-implemented sometime in the future…

General

• Improved layout (vertical alignment) for some plotting-functions for the bayestestR-package, when there was only one parameter. Plots now are closer to the x-axis, removing unnecessary empty space.

• Labels and plot annotations are now more “human readable”, and labelling is more context sensitive.

New plot-functions

• Added coord_radar for radar charts.

• Added plot-function for parameters::cluster_analysis().

• Added plot-function for parameters::principal_components().

• Added plot-function for parameters::parameters_simulate().

• Added plot-function for parameters::n_factors().

• Added plot-function for bayestestR::p_significance().

Changes to functions

• plot() for parameters::model_parameters() gets a sort-argument to sort coefficients.

• plot() for parameters::model_parameters() now also create forest plots for meta-analysis.

• plot() for bayestestR::bayesfactor_parameters() only plots facets when necessary.

• plot() for performance::check_outliers() now also plot multiple methods in one plot.

• Following plot() methods get a n_columns-argument, so model components like random effects or a zero-inflation component can be plotted in a multi-column layout: bayestestR::p_direction(), bayestestR::hdi(), bayestestR::rope(), bayestestR::equivalence_test(), parameters::model_parameter(), parameters::parameters_simulate()

• Following plot() methods get priors and priors_alpha arguments, to add a layer with prior samples to the plot: bayestestR::p_direction(), bayestestR::estimate_density(), bayestestR::point_estimate()

see 0.2.1

CRAN release: 2019-08-01

General

• More comprehensive examples available from the package-website.

• Added new color-palettes.

New plot-functions

• Added plot-function for parameters::model_parameters().

• Added plot-function for bayestestR::point_estimate().

Changes to functions

• The plot()-method for bayestestR::bayesfactor_savagedickey() gets a rope_color and a rope_alpha-argument to plot the “null”-interval, when the null-hypothesis is a region of practical equivalence, and not just the point-null.

• The plot()-method for performance::binned_residuals() now also allows to modify size and colors of geoms (related arguments are in performance::binned_residuals()).

Bug fixes

• Fixed issue with dark themes and text color in facet headings.

see 0.2.0

CRAN release: 2019-06-19

General

• geom_point2() now accepts size-aesthetics when mapped to data.

• Themes now get a base_size and base_family argument, in line with ggplot themes, to set the default size and family for plots.

• plot()-methods now work for bayestestR functions that work on emmGrid-objects (created from pairwise comparison with package emmeans).

New themes

• theme_lucid(), a light and clear theme.

New plot-functions

• Added plot-function for performance::check_model().

• Added plot-function for performance::check_normality().

• Added plot-function for performance::check_heteroscedasticity().

• Added plot-function for performance::check_outliers().

• Added plot-function for performance::check_distribution().

• Added plot-function for performance::check_collinearity().

• Added plot-function for performance::check_homogeneity().

New geoms

• geom_poolpoint() and geom_pooljitter() to draw pool ball points (points labelled with the observation name).

Bug fixes

• Fixed issues with color codes in the flat-ui palette.