humind
The MSNI humanitarian needs framework as code, rewritten and re-broken every year
A side-by-side editorial comparison of inlabru and predictsr — release velocity, themes, recent moves, and the top alternatives to consider.
A Bayesian spatial modelling package rebuilding its foundations one breaking release at a time
inlabru wraps INLA for spatial, point-process and latent-Gaussian models in R. It is mid-modernisation: since 2.12.0 cut the sp stack, each release has renamed part of the public surface, standardised how external packages attach custom mappers, or replaced internal machinery. 2.15.0 is the latest step, pairing a new predictor evaluation and linearisation implementation with broom's tidy(), glance() and augment() methods and four non-zero-truncated observation families.
A single visible release: the PREDICTS data client patching its download path.
predictsr provides R access to the PREDICTS biodiversity database hosted on the Natural History Museum data portal. Only one release is visible in the feed, 0.2.1, which repairs an API error originating on the portal side and tightens the download path: temporary files are now cleaned up when a download fails, year comparisons no longer compare integers incorrectly, and SHA validation no longer fails on missing values. With one entry there is no cadence to read and no arc to describe.
inlabru wraps INLA for spatial, point-process and latent-Gaussian models in R. It is mid-modernisation: since 2.12.0 cut the sp stack, each release has renamed part of the public surface, standardised how external packages attach custom mappers, or replaced internal machinery. 2.15.0 is the latest step, pairing a new predictor evaluation and linearisation implementation with broom's tidy(), glance() and augment() methods and four non-zero-truncated observation families.
The arc is consolidation of the extension surface rather than expansion of the model catalogue. Every release adds mappers or families with one hand and removes a dependency, a re-export or a deprecated path with the other — plyr in 2.15.0, fmesher's Depends entry in 2.14.1, sp and ggmap in 2.12.0. The compatibility flag bru_compat_pre_2_14_enable and the temporary fm_int/fm_pixels re-exports show a maintainer sequencing breaks across releases instead of landing them together.
The 2.14 compatibility flag is still defaulting to TRUE and the fmesher re-exports are described in the entries as temporary, so the next obvious move is a release that flips bru_compat_pre_2_14_enable off and drops those re-exports.
predictsr provides R access to the PREDICTS biodiversity database hosted on the Natural History Museum data portal. Only one release is visible in the feed, 0.2.1, which repairs an API error originating on the portal side and tightens the download path: temporary files are now cleaned up when a download fails, year comparisons no longer compare integers incorrectly, and SHA validation no longer fails on missing values. With one entry there is no cadence to read and no arc to describe.
What can be said from a single release is that the package's failure modes are concentrated where it meets the data portal rather than in its own analysis code, and that the fixes are the kind found by users hitting real downloads: leftover temporary files, checksum validation tripping over NAs, an upstream API change. The adoption of the air formatter and a GitHub Actions check in the same release suggests maintenance tooling being put in place rather than a feature programme.
Too little is visible here to predict a direction with any confidence. The one signal worth noting is that this release was largely reactive to a portal-side change, so future releases are likely to track the data portal's behaviour rather than follow a roadmap of the package's own.
Other Infra & APIs 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 inlabru or predictsr.
The MSNI humanitarian needs framework as code, rewritten and re-broken every year
UK government chart styling in ggplot2, chasing ggplot2 v4 and stretching its palette to five.
A gamma-convolution density package that reached completion in 2018 and has coasted since.
Animal-movement models in R, where new stochastic processes arrive years apart.
A basic DNA and RNA sequence toolkit that went quiet for three years, then jumped to 2.0.
Package citation for R documents, quietly growing to meet Quarto.
See all inlabru alternatives → · See all predictsr alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-package — within Infra & APIs. inlabru is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. inlabru is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. For your specific use case, the alternatives sections above list other Infra & APIs products to evaluate alongside.
Top inlabru alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "inlabru alternatives" section above for the current picks, or visit /alternatives/inlabru for the full list with editorial commentary on each.
Top predictsr alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "predictsr alternatives" section above for the current picks, or visit /alternatives/predictsr for the full list with editorial commentary on each.