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Comparison · Infra & APIs
inlabru vs plssem
A side-by-side editorial comparison of inlabru and plssem — release velocity, themes, recent moves, and the top alternatives to consider.
inlabru vs plssem: at a glance
| Feature | inlabru | plssem |
|---|---|---|
| Sector | Infra & APIs | Infra & APIs |
| Velocity score | 2.5 | 0.0 |
| Sparks · 30d | 0 | 0 |
| Top themes | bayesian-modelling, spatial-statistics, r-package, api-consolidation | structural-equation-modeling, partial-least-squares, multilevel-models, standard-errors |
| Last editorial update | 3h ago | 1h ago |
| Website | Visit → | Visit → |
What is inlabru?
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.
What is plssem?
plssem took PLS-SEM into multilevel data, then spent two releases making the estimates trustworthy.
plssem is a young R implementation of partial least squares structural equation modelling, three CRAN releases old and shipping monthly. Its distinguishing work is the MC-PLS family — consistent PLS estimators the maintainer extended to mixed-effects designs in June — and the releases since have been about getting standard errors, admissibility and fit measures onto the same footing as the point estimates.
inlabru vs plssem: editorial side-by-side
inlabru
2.5INFRA · APIS
A Bayesian spatial modelling package rebuilding its foundations one breaking release at a time
◆ Current state
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.
◆ Where it's heading
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.
◆ Prediction
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.
plssem
0.0INFRA · APIS
plssem took PLS-SEM into multilevel data, then spent two releases making the estimates trustworthy.
◆ Current state
plssem is a young R implementation of partial least squares structural equation modelling, three CRAN releases old and shipping monthly. Its distinguishing work is the MC-PLS family — consistent PLS estimators the maintainer extended to mixed-effects designs in June — and the releases since have been about getting standard errors, admissibility and fit measures onto the same footing as the point estimates.
◆ Where it's heading
The pattern is capability first, inference second. Multilevel MC-PLSc and MC-OrdPLSc arrived in 0.1.2 together with Monte-Carlo delta-method standard errors and a Polyak-Juditsky extrapolation step; 0.1.3 then extended delta-method errors to redundant parameters and thresholds, optimized their computation, added a loglikelihood-based fit measure and generated dynamic bounds to keep MC-PLS solutions admissible. Admissibility recurs throughout — penalized inadmissible solutions in 0.1.1, variance lower bounds and negative residual variance handling in 0.1.3, and an option to drop inadmissible bootstraps rather than silently include them. The release notes are pull-request lists, so the reasoning behind each change stays in the repository.
◆ Prediction
The MIMIC mode and GLS estimator both landed in the most recent release without the standard-error and fit-measure work that followed earlier additions, so extending inference to cover them is the natural next step. Bootstrap defaults moving to 500 replications suggests runtime is a live constraint and further optimization is likely.
Alternatives to inlabru and plssem
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 plssem.
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Six months of releases and not one of them touched the scoring models
samplr
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stochvol
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midr
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See all inlabru alternatives → · See all plssem alternatives →
Recent activity from inlabru and plssem
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 23d agoinlabruPredictor linearisation rewritten; broom tidiers, truncated families
- 1mo agoplssemMIMIC mode, a GLS structural estimator and delta-method thresholds
- 2mo agoplssemMC-PLSc and MC-OrdPLSc extend to multilevel and mixed-effects models ⚡
- 3mo agoinlabruBugfix release: factor contrasts, raster extraction, error classes
- 3mo agoplssemParallel bootstrapping, kNN and mean imputation, higher-order constructs
- 5mo agoinlabruNew mappers, standardised cgeneric support, bru_obs storage refactor
- 1y agoinlabruMapper classes shortened to bm_*, experimental predictor aggregation
- 1y agoinlabruDrops sp and ggmap for an sf-native spatial stack ⚡
Frequently asked questions
What is the difference between inlabru and plssem?
They serve adjacent needs but don't currently overlap on shipped themes. 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.
Is inlabru better than plssem?
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.
What are the best alternatives to inlabru?
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.
What are the best alternatives to plssem?
Top plssem alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "plssem alternatives" section above for the current picks, or visit /alternatives/plssem for the full list with editorial commentary on each.