Vectorised Probability Distributions
Overview
Vectorised distribution objects with tools for manipulating, visualising, and using probability distributions. Designed to allow model prediction outputs to return distributions rather than their parameters, allowing users to directly interact with predictive distributions in a data-oriented workflow. In addition to providing generic replacements for p/d/q/r functions, other useful statistics can be computed including means, variances, intervals, and highest density regions.
New features
- Added a
vignette("broadcasting")to describe how statistics apply to vectors of distributions differently based on the form of the statistical operation's argument (scalar, vector, or list). - Added
dist_density(), a distribution characterised by the values of its probability density function at a set of points. This is useful for representing a distribution known only through its density, such as a kernel density estimate or a posterior evaluated over a grid. - Added
dist_cdf(), which describes a distribution by the cumulative probabilities at a set of values. Interpolation is done linearly, and the results are equivalent todist_quantile()with swapped arguments. - Added
dist_tweedie(), for the Tweedie compound Poisson-Gamma distribution with power parameter in(1, 2), using thetweedieDistrpackage (@StefanoDamato).
Show all changes in 0.9.0Hide the rest of the changes in 0.9.0
- Added
recursiveoption forparameters(), which recursively extracts the parameters of inner distributions to return a flat data frame (#161). - Added
recursiveoption forfamily(), which identifies the families of distributions embedded within another (e.g.dist_mixture()) returning a nested list describing the full family tree (#110).
Breaking changes
generate()'stimesargument no longer accepts length-n vectors, and instead requirestimes = list(c(...))for consistency with other operations.
From NEWS.md in the release
Install
Health
- OK13 OK2026-08-05
- NOTE12 OK, 1 NOTE2026-08-01
- OK14 OK2026-03-10
Documentation
- Help pages
- 81 (2 internal)includes a package overview page
- Examples that run
- 100%58 run in a plain check (15 of them under a condition)
- Exported functions with examples
- 83%
- Documented parameters
- 80%
- Return-value docs
- 7%
- Help pages citing references
- 5%
- Broadcasting rules HTML
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Repository
- PRs merged (all time)
- 86%
- Median days to close, 50 most recently updated closed issues
- 25
- Median days to close, 50 most recently updated closed PRs
- 6
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Checks run against github.com/mitchelloharawild/distributional on 2026-10-11.
The R CMD check workflow runs on Linux, macOS and Windows, and on R-devel
GitHub Pages site last deployed 2026-10-09 · The repository has a site deploy workflow
pkgdown site last built 2026-09-08
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Dependencies
Installing distributional adds 9 packages (5 with compiled code, 3.3 MB of source tarballs). Heaviest: vctrs 1.0 MB, rlang 766 KB, cli 629 KB.
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Code & Tests
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Pick two releases to compare their code metrics.
- 0.9.0Latest
- 0.8.12026-06-27 · diff ↗
- 0.8.0
- 0.7.12026-06-11 · diff ↗
- RR 4.6.0 released · 2026-04-24
- 0.7.0
- 0.6.0
- RR 4.5.0 released · 2025-04-11
- 0.5.0
- RR 4.4.0 released · 2024-04-24
- 0.4.02024-02-07 · diff ↗ ·
removed 6 exports
autoplot.distribution, geom_hilo_linerange, geom_hilo_ribbon, guide_level, scale_hilo_continuous, scale_level_continuous - RR 4.3.0 released · 2023-04-21
- 0.3.22023-03-22 · diff ↗
- 0.3.12022-09-02 · diff ↗
- RR 4.2.0 released · 2022-04-22
- 0.3.02022-01-06 · diff ↗ ·
added 7 exports
autoplot.distribution, covariance, dist_categorical, dist_lognormal, log_likelihood, parameters, support
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- RR 4.1.0 released · 2021-05-18
- 0.2.2
- 0.2.1
- 0.2.02020-08-03 · diff ↗ ·
removed 2 exports
col2hex, darken_filladded 4 exports
dist_wrap, kurtosis, likelihood, skewness - 0.1.02020-06-09
- RR 4.0.0 released · 2020-04-24
Package metadata
- First published
- 2020-06-09
- Total releases
- 15 / 6 yrs
- License
- GPL-3 OSI
- Minimum R
- ≥ 4.0.0
- Download size
- 183 KB
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