ggdist - Visualizations of Distributions and Uncertainty

Provides primitives for visualizing distributions using 'ggplot2' that are particularly tuned for visualizing uncertainty in either a frequentist or Bayesian mode. Both analytical distributions (such as frequentist confidence distributions or Bayesian priors) and distributions represented as samples (such as bootstrap distributions or Bayesian posterior samples) are easily visualized. Visualization primitives include but are not limited to: points with multiple uncertainty intervals, eye plots (Spiegelhalter D., 1999) <https://ideas.repec.org/a/bla/jorssa/v162y1999i1p45-58.html>, density plots, gradient plots, dot plots (Wilkinson L., 1999) <doi:10.1080/00031305.1999.10474474>, quantile dot plots (Kay M., Kola T., Hullman J., Munson S., 2016) <doi:10.1145/2858036.2858558>, complementary cumulative distribution function barplots (Fernandes M., Walls L., Munson S., Hullman J., Kay M., 2018) <doi:10.1145/3173574.3173718>, and fit curves with multiple uncertainty ribbons.

Last updated 3 months ago

ggplot2uncertaintyuncertainty-visualizationvisualizationcpp

15.24 score 856 stars 61 dependents 3.1k scripts 33k downloads

tidybayes - Tidy Data and 'Geoms' for Bayesian Models

Compose data for and extract, manipulate, and visualize posterior draws from Bayesian models ('JAGS', 'Stan', 'rstanarm', 'brms', 'MCMCglmm', 'coda', ...) in a tidy data format. Functions are provided to help extract tidy data frames of draws from Bayesian models and that generate point summaries and intervals in a tidy format. In addition, 'ggplot2' 'geoms' and 'stats' are provided for common visualization primitives like points with multiple uncertainty intervals, eye plots (intervals plus densities), and fit curves with multiple, arbitrary uncertainty bands.

Last updated 5 months ago

bayesian-data-analysisbrmsggplot2jagsstantidy-datavisualization

14.88 score 732 stars 19 dependents 7.3k scripts 6.2k downloads

ARTool - Aligned Rank Transform

The aligned rank transform for nonparametric factorial ANOVAs as described by Wobbrock, Findlater, Gergle, and Higgins (2011) <doi:10.1145/1978942.1978963>. Also supports aligned rank transform contrasts as described by Elkin, Kay, Higgins, and Wobbrock (2021) <doi:10.1145/3472749.3474784>.

Last updated 3 years ago

8.43 score 59 stars 255 scripts 1.8k downloads

ggblend - Blending and Compositing Algebra for 'ggplot2'

Algebra of operations for blending, copying, adjusting, and compositing layers in 'ggplot2'. Supports copying and adjusting the aesthetics or parameters of an existing layer, partitioning a layer into multiple pieces for re-composition, applying affine transformations to layers, and combining layers (or partitions of layers) using blend modes (including commutative blend modes, like multiply and darken). Blend mode support is particularly useful for creating plots with overlapping groups where the layer drawing order does not change the output; see Kindlmann and Scheidegger (2014) <doi:10.1109/TVCG.2014.2346325>.

Last updated 2 years ago

6.39 score 183 stars 1 dependents 89 scripts 378 downloads