compositional.mle
An MLE package rebuilt around composable solvers, then renamed to match.
Comparison · Analytics
hubEvals vs INBOmd
A side-by-side editorial comparison of hubEvals and INBOmd — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-package
hubEvals vs INBOmd: at a glance
What is hubEvals?
Forecast-hub scoring that learned to handle joint, sample-based predictions.
hubEvals scores model output from collaborative forecasting hubs, wrapping scoringutils and translating hubverse formats into forecast objects it can evaluate. The package has moved quickly from a thin translation layer to something that handles every output type the hubverse defines — quantile, mean, median, nominal and ordinal pmf, and samples. The most recent releases are almost entirely about the failure modes of relative skill scoring rather than about new metrics.
What is INBOmd?
Institutional report templates where a missing metadata field watermarks the whole document.
INBOmd supplies R Markdown output formats — PDF, gitbook, EPUB — carrying the house style and colophon requirements of INBO, the Flemish nature and forest research institute. Its distinguishing design decision is enforcement by embarrassment: an incomplete colophon stamps a watermark across every page until the required fields are filled in. Recent releases are small corrections, with the substantive template work sitting several years back.
hubEvals vs INBOmd: editorial side-by-side
hubEvals
2.5ANALYTICS
Forecast-hub scoring that learned to handle joint, sample-based predictions.
◆ Current state
hubEvals scores model output from collaborative forecasting hubs, wrapping scoringutils and translating hubverse formats into forecast objects it can evaluate. The package has moved quickly from a thin translation layer to something that handles every output type the hubverse defines — quantile, mean, median, nominal and ordinal pmf, and samples. The most recent releases are almost entirely about the failure modes of relative skill scoring rather than about new metrics.
◆ Where it's heading
Two threads dominate. The first is coverage of output types, which reached its widest point with sample-based and compound scoring. The second, and the one occupying every recent release, is making relative skill degrade gracefully: single-model input, comparison groups with one model, and groups missing the requested baseline have each been converted from a cryptic upstream abort into a defined result. That pattern — inherited scoringutils errors being caught and given hub-specific meaning — is the clearest signal of where this package adds value.
◆ Prediction
Expect continued work smoothing scoringutils error surfaces into hub-aware behaviour, and performance attention on relative skill, which was explicitly optimised in the latest release.
INBOmd
0.0ANALYTICS
Institutional report templates where a missing metadata field watermarks the whole document.
◆ Current state
INBOmd supplies R Markdown output formats — PDF, gitbook, EPUB — carrying the house style and colophon requirements of INBO, the Flemish nature and forest research institute. Its distinguishing design decision is enforcement by embarrassment: an incomplete colophon stamps a watermark across every page until the required fields are filled in. Recent releases are small corrections, with the substantive template work sitting several years back.
◆ Where it's heading
The package has settled into maintenance around a stable feature set, with recent activity split between watermark and colophon edge cases and keeping in step with its siblings — it picked up the new citeme dependency within days of checklist splitting that package out. The open work is the long tail of citation rendering across three output formats, where subtitles, colophon fields and DOIs each surface separately. Nothing here suggests new output formats are planned.
◆ Prediction
Expect continued small fixes to colophon and citation rendering across the three output formats, and dependency updates tracking the checklist and citeme packages it sits alongside.
Alternatives to hubEvals and INBOmd
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 hubEvals or INBOmd.
nabla
nabla dropped its C++ engine to chase exact derivatives at any order.
snowflakeauth
Eight months from first release to keyring caching and workload identity.
kwb.geosalz
A research-project workflow package where the interesting work is in the plumbing.
cyclocomp
A cyclomatic complexity checker that ships once every couple of years, and lands when it does.
revdbayes
Extreme value sampling in pure upkeep mode, mostly answering to Rcpp and CRAN.
See all hubEvals alternatives → · See all INBOmd alternatives →
Recent activity from hubEvals and INBOmd
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 24d agohubEvalsScored-forecast counts and faster relative skill
- 1mo agohubEvalsDisaggregated relative skill no longer aborts the whole call
- 1mo agoINBOmdWatermark no longer prints NA when colophon fields are missing
- 1mo agohubEvalsSingle-model scoring returns relative skill of 1 instead of erroring
- 1mo agoINBOmdDependency bump to the latest citeme and checklist
- 5mo agohubEvalsSample output types and multivariate compound scoring ⚡
- 5mo agoINBOmdMissing subtitle restored in gitbook and EPUB colophon citations
- 6mo agohubEvalsScoring on transformed scales via transform arguments
- 11mo agohubEvalsFirst release: score_model_out() and the scoringutils bridge
- 2y agoINBOmdpdf_report() requires pandoc 3.1.8 or later
- 2y agoINBOmdWatermarks and separate colophons for internal reports
- 3y agoINBOmdStructured author metadata required; interactive report helpers added
Frequently asked questions
What is the difference between hubEvals and INBOmd?
Both compete on the same themes — r-package — within Analytics. hubEvals 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 hubEvals better than INBOmd?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. hubEvals 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 Analytics products to evaluate alongside.
What are the best alternatives to hubEvals?
Top hubEvals alternatives in Analytics are ranked by recent ship velocity. Browse the "hubEvals alternatives" section above for the current picks, or visit /alternatives/hubevals for the full list with editorial commentary on each.
What are the best alternatives to INBOmd?
Top INBOmd alternatives in Analytics are ranked by recent ship velocity. Browse the "INBOmd alternatives" section above for the current picks, or visit /alternatives/inbomd for the full list with editorial commentary on each.