compositional.mle
An MLE package rebuilt around composable solvers, then renamed to match.
Comparison · Analytics
checklist vs hubEvals
A side-by-side editorial comparison of checklist and hubEvals — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-package
checklist vs hubEvals: at a glance
What is checklist?
An institutional R quality-control package that just split its citation half into its own tool.
checklist enforces coding, documentation and metadata standards for R packages and projects at INBO, the Flemish research institute for nature and forest, and runs as both a local tool and a GitHub Action. Much of its work concerns research-output metadata — Zenodo deposits, DOIs, ORCID, ROR identifiers, organisation records — rather than code style. Its most recent major release removed that entire area from the package.
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.
checklist vs hubEvals: editorial side-by-side
checklist
0.0ANALYTICS
An institutional R quality-control package that just split its citation half into its own tool.
◆ Current state
checklist enforces coding, documentation and metadata standards for R packages and projects at INBO, the Flemish research institute for nature and forest, and runs as both a local tool and a GitHub Action. Much of its work concerns research-output metadata — Zenodo deposits, DOIs, ORCID, ROR identifiers, organisation records — rather than code style. Its most recent major release removed that entire area from the package.
◆ Where it's heading
The direction is decomposition. An organisation class was first superseded by a more structured pair of classes, and then the whole citation and deposit surface moved out to a separate citeme package, leaving checklist focused on project and package checking. The sibling INBOmd package picked up the new dependency within a week, which is how this family propagates a change. What remains here is narrower and more clearly named than what it started with.
◆ Prediction
Expect checklist to continue tightening its remaining project-checking scope, with further citation and metadata work landing in citeme rather than here.
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.
Alternatives to checklist and hubEvals
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 checklist or hubEvals.
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 checklist alternatives → · See all hubEvals alternatives →
Recent activity from checklist and hubEvals
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 agohubEvalsSingle-model scoring returns relative skill of 1 instead of erroring
- 1mo agochecklistOrganisation now passed correctly when creating a package skeleton
- 1mo agochecklistCitation and Zenodo functions split out into the citeme package ⚡
- 5mo agohubEvalsSample output types and multivariate compound scoring ⚡
- 5mo agochecklistZenodo deposits gain publisher, EU grant IDs and ROR handling
- 6mo agohubEvalsScoring on transformed scales via transform arguments
- 7mo agochecklistContributing and conduct files created only when requested
- 8mo agochecklistGitHub Action restores renv environments and installs system dependencies
- 8mo agochecklistorganisation class superseded by org_list and org_item
- 11mo agohubEvalsFirst release: score_model_out() and the scoringutils bridge
Frequently asked questions
What is the difference between checklist and hubEvals?
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 checklist better than hubEvals?
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 checklist?
Top checklist alternatives in Analytics are ranked by recent ship velocity. Browse the "checklist alternatives" section above for the current picks, or visit /alternatives/checklist for the full list with editorial commentary on each.
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.