qqman
The Manhattan-plot package for GWAS results, finished and dormant since 2017.
Comparison · Analytics
fossilsim vs weird
A side-by-side editorial comparison of fossilsim and weird — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-package
fossilsim vs weird: at a glance
What is fossilsim?
A fossil-record simulator that quietly grew a trait-evolution engine.
FossilSim is a mature R package for simulating fossil records on phylogenetic trees, and its release cadence reflects that: long gaps punctuated by a single capability addition. The last four releases span three years, with the most recent being a compatibility sync to its companion Shiny front-end rather than new functionality. The core simulation surface has been stable since 2022.
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.
fossilsim vs weird: editorial side-by-side
fossilsim
0.0ANALYTICS
A fossil-record simulator that quietly grew a trait-evolution engine.
◆ Current state
FossilSim is a mature R package for simulating fossil records on phylogenetic trees, and its release cadence reflects that: long gaps punctuated by a single capability addition. The last four releases span three years, with the most recent being a compatibility sync to its companion Shiny front-end rather than new functionality. The core simulation surface has been stable since 2022.
◆ Where it's heading
The arc runs from sampling mechanics toward simulating what the organisms actually were. Version 2.2.0 taught the package to handle occurrence data for occurrence birth-death models; 2.3.0 then added trait simulation under Mk, BM and OU, which is a different kind of output than fossil ages. Since then the work has been maintenance and keeping the FossilSimShiny GUI in step, suggesting the authors consider the current model set feature-complete.
◆ Prediction
The pairing of the 2.3.3 release with a FossilSimShiny version bump points to the GUI, not the library, as where the next visible work lands. The entries do not show enough activity to predict a specific new model family.
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 fossilsim 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 fossilsim or weird.
constants
The R package for CODATA constants rebuilt its symbol table on NIST's naming so future updates stop being hand work.
austraits
The R client for AusTraits spends its releases chasing the dataset it reads.
ggdemetra
A ggplot2 layer for seasonal adjustment output, filling in one plot type at a time.
tern.rbmi
Reference-based multiple imputation tables, shipping only what CRAN checks demand.
tern.mmrm
An MMRM tabulation package that has published nothing since its 2024 CRAN releases.
See all fossilsim alternatives → · See all weird alternatives →
Recent activity from fossilsim 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
- 6mo agoweirdPackage refactored onto distributional objects; density_scores becomes surprisals
- 2y agofossilsimCompatibility bump for FossilSimShiny 1.1.2
- 2y agoweirdWine reviews dataset replaced with a fetch function
- 4y agofossilsimBug fixes and documentation cleanup
- 4y agofossilsimTrait simulation arrives: Mk, BM and OU models ⚡
- 5y agofossilsimOccurrence handling for the occurrence birth-death model
Frequently asked questions
What is the difference between fossilsim and weird?
Both compete on the same themes — r-package — within Analytics. fossilsim 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 fossilsim better than weird?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. fossilsim 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 fossilsim?
Top fossilsim alternatives in Analytics are ranked by recent ship velocity. Browse the "fossilsim alternatives" section above for the current picks, or visit /alternatives/fossilsim-r 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.