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mjskay
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Visualizations of distributions and uncertainty

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ggdist: Visualizations of distributions and uncertainty

R build
status Coverage
status CRAN
status Download count DOI

Preview of ggdist plots

ggdist is an R package that provides a flexible set of

ggplot2
geoms and stats designed especially for visualizing distributions and uncertainty. It is designed for both frequentist and Bayesian uncertainty visualization, taking the view that uncertainty visualization can be unified through the perspective of distribution visualization: for frequentist models, one visualizes confidence distributions or bootstrap distributions (see
vignette("freq-uncertainty-vis")
); for Bayesian models, one visualizes probability distributions (see the tidybayes package, which builds on top of
ggdist
).

The

geom_slabinterval()
/
stat_slabinterval()
/
stat_dist_slabinterval()
family (see
vignette("slabinterval")
) includes point summaries and intervals, eye plots, half-eye plots, CCDF bar plots, gradient plots, dotplots, and histograms:

The slabinterval family of geoms and
stats

The

geom_lineribbon()
/
stat_lineribbon()
/
stat_dist_lineribbon()
family (see
vignette("lineribbon")
) makes it easy to visualize fit lines with an arbitrary number of uncertainty bands:

<!-- -->

All geoms in

ggdist
also have
stat_dist_
counterparts designed for visualizing analytical distributions, which is particularly useful when visualizing uncertainty in frequentist models (see
vignette("freq-uncertainty-vis")
) or when visualizing priors in a Bayesian analysis.

The

ggdist
geoms and stats also form a core part of the tidybayes package (in fact, they originally were part of
tidybayes
). For examples of the use of
ggdist
geoms and stats for visualizing uncertainty in Bayesian models, see the vignettes in tidybayes, such as
vignette("tidybayes", package = "tidybayes")
or
vignette("tidy-brms", package = "tidybayes")
.

Cheat sheets

Installation

You can install the currently-released version from CRAN with this R command:

install.packages("ggdist")

Alternatively, you can install the latest development version from GitHub with these R commands:

install.packages("devtools")
devtools::install_github("mjskay/ggdist")

Feedback, issues, and contributions

I welcome feedback, suggestions, issues, and contributions! Contact me at [email protected]. If you have found a bug, please file it here with minimal code to reproduce the issue. Pull requests should be filed against the

dev
branch.

Citing
ggdist

Matthew Kay (2020). ggdist: Visualizations of Distributions and Uncertainty. R package version 2.4.0, https://mjskay.github.io/ggdist/. DOI: 10.5281/zenodo.3879620.

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