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Comparison · Analytics
epiworldR vs weird
A side-by-side editorial comparison of epiworldR and weird — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-package
epiworldR vs weird: at a glance
What is epiworldR?
epiworldR is a thin R shell whose releases track the C++ simulator underneath it
Almost every release here is a version bump of the underlying epiworld C++ library, wrapped and pushed to CRAN. The substantive R-side work is narrow and consistent: exposing simulation outputs that were already computed but not reachable from R — outbreak size, active cases, hospitalizations and their savers. The newest release addresses an AddressSanitizer finding, which is the kind of thing CRAN checks surface on a compiled package.
What is weird?
weird rebuilt itself on distributional objects, and now the anomaly tooling composes with everything else.
An R package for anomaly detection and unusual-observation diagnostics, at four releases with a long gap between the 2024 patch and the 2026 major line. The current shape is set by 2.0.0, which refactored the package onto distributional objects and renamed its central concept from density_scores() to surprisals(). Since then the work has been filling that structure in: surprisals for more model classes, faster bandwidth and probability calculations, and new visual diagnostics.
epiworldR vs weird: editorial side-by-side
epiworldR
0.0ANALYTICS
epiworldR is a thin R shell whose releases track the C++ simulator underneath it
◆ Current state
Almost every release here is a version bump of the underlying epiworld C++ library, wrapped and pushed to CRAN. The substantive R-side work is narrow and consistent: exposing simulation outputs that were already computed but not reachable from R — outbreak size, active cases, hospitalizations and their savers. The newest release addresses an AddressSanitizer finding, which is the kind of thing CRAN checks surface on a compiled package.
◆ Where it's heading
The R package's job is staying current with the simulator and satisfying CRAN, not evolving its own interface. What direction it has shows in which model outputs get exposed next, and in a steady tidy-up of the build — the custom configure script was dropped in favour of R's built-in C++17 and OpenMP settings, and test coverage has been filled in across several releases with automated assistance.
◆ Prediction
Expect the next release to track another epiworld version bump, with any R-side addition most likely being one more exposed metric or saver, following the pattern of get_hospitalizations and get_outbreak_size.
weird
0.0ANALYTICS
weird rebuilt itself on distributional objects, and now the anomaly tooling composes with everything else.
◆ Current state
An R package for anomaly detection and unusual-observation diagnostics, at four releases with a long gap between the 2024 patch and the 2026 major line. The current shape is set by 2.0.0, which refactored the package onto distributional objects and renamed its central concept from density_scores() to surprisals(). Since then the work has been filling that structure in: surprisals for more model classes, faster bandwidth and probability calculations, and new visual diagnostics.
◆ Where it's heading
The refactor onto a shared distribution representation is the decision everything else follows from. It let 2.1.0 add hdr() and parameters() methods for kde objects rather than bespoke accessors, and it let 3.0.0 bring in dist_mclust() to turn a Gaussian mixture model into the same object type — so a mixture, a kernel density estimate and a fitted distribution all flow through one interface. The 3.0.0 additions lean visual and multivariate: outlier maps plotting score distance against orthogonal distance, biplot projections with variable axes overlaid, and an augment() method for robust PCA objects. Dependencies have been shed steadily along the way — lookout, interpolation — while mvscale() moved out and then back in.
◆ Prediction
Expect surprisals() coverage to keep extending to further model classes, and the multivariate and robust-PCA diagnostics introduced in 3.0.0 to gain the same distributional-object treatment as the univariate side.
Alternatives to epiworldR and weird
Other Analytics products tracked by Sparkpulse, ranked by recent ship velocity. Each card links to a full editorial trajectory and lets you pivot into a head-to-head comparison with either epiworldR or weird.
tidytransit
tidytransit tracks the GTFS spec as it grows, one reader and one router feature at a time.
oblicubes
A tiny grid renderer for oblique-projection cubes, complete since its first release.
biocro
BioCro swapped an unstable iteration for real root finders, changing what its crop models compute.
redist
redist keeps rewriting the sampler underneath a district-drawing API it has held stable since 4.0.
epiflows
epiflows has shipped four releases in eight years, none of which changed the code.
See all epiworldR alternatives → · See all weird alternatives →
Recent activity from epiworldR and weird
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 1mo agoweirdOutlier maps, biplot projections, and Gaussian mixtures as distributional objects
- 3mo agoweirdsurprisals() reaches glm objects; lookout dependency dropped
- 4mo agoepiworldR0.14.0 addresses an AddressSanitizer finding
- 5mo agoepiworldRWrapper bumped to track a new epiworld version
- 5mo agoepiworldRBuild drops the custom configure script for R's C++17 and OpenMP settings
- 6mo agoepiworldRepiworld bumped to 0.11.2
- 6mo agoweirdPackage refactored onto distributional objects; density_scores becomes surprisals
- 7mo agoepiworldRTests updated at CRAN's request
- 7mo agoepiworldRHospitalizations, outbreak size and active cases exposed to R
- 2y agoweirdWine reviews dataset replaced with a fetch function
Frequently asked questions
What is the difference between epiworldR and weird?
Both compete on the same themes — r-package — within Analytics. epiworldR and weird are shipping at a similar cadence (velocity 0.0 vs 0.0, both within Sparkpulse's "active" band). See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.
Is epiworldR better than weird?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. epiworldR and weird are shipping at a similar cadence (velocity 0.0 vs 0.0, both within Sparkpulse's "active" band). For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.
What are the best alternatives to epiworldR?
Top epiworldR alternatives in Analytics are ranked by recent ship velocity. Browse the "epiworldR alternatives" section above for the current picks, or visit /alternatives/epiworldr for the full list with editorial commentary on each.
What are the best alternatives to weird?
Top weird alternatives in Analytics are ranked by recent ship velocity. Browse the "weird alternatives" section above for the current picks, or visit /alternatives/weird-r for the full list with editorial commentary on each.