compositional.mle
An MLE package rebuilt around composable solvers, then renamed to match.
Comparison · Analytics
hubEvals vs libr
A side-by-side editorial comparison of hubEvals and libr — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-package
hubEvals vs libr: 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 libr?
The SAS datastep clone for R just got roughly nineteen times faster.
libr gives R users SAS-style data libraries and a datastep() construct, sitting alongside logr, reporter and procs in the r-sassy suite for analysts moving clinical workflows off SAS. Most of its release history is narrow bug-fixing in the libname() readers, particularly the sas7bdat engine. The exception dominates the window: a single 2026 release that rewrote datastep() performance and cut the installed package to a quarter of its former size.
hubEvals vs libr: 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.
libr
2.5ANALYTICS
The SAS datastep clone for R just got roughly nineteen times faster.
◆ Current state
libr gives R users SAS-style data libraries and a datastep() construct, sitting alongside logr, reporter and procs in the r-sassy suite for analysts moving clinical workflows off SAS. Most of its release history is narrow bug-fixing in the libname() readers, particularly the sas7bdat engine. The exception dominates the window: a single 2026 release that rewrote datastep() performance and cut the installed package to a quarter of its former size.
◆ Where it's heading
Two threads run through these entries — steady correctness work on SAS file import, and a much less frequent but far more consequential push on making datastep() viable at real data volumes. The recent fix to empty-variable typing suggests the sas7bdat reader is still where edge cases surface. Having addressed both speed and package size in one release, the obvious remaining pressure is correctness and coverage of SAS semantics rather than throughput.
◆ Prediction
Expect the next releases to continue narrowing sas7bdat import edge cases, with any further datastep() work aimed at supporting more SAS syntax rather than at speed.
Alternatives to hubEvals and libr
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 libr.
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 libr alternatives →
Recent activity from hubEvals and libr
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 11d agolibrsas7bdat import no longer types empty variables as logical
- 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
- 3mo agolibrdatastep() runs 83K rows in 21.6 seconds instead of 6.7 minutes ⚡
- 5mo agohubEvalsSample output types and multivariate compound scoring ⚡
- 5mo agolibrTest data removed to reduce package size
- 6mo agohubEvalsScoring on transformed scales via transform arguments
- 11mo agohubEvalsFirst release: score_model_out() and the scoringutils bridge
- 2y agolibrlibname() no longer fails on an empty dataset
- 2y agolibrlib_write() detects dataset changes again
- 2y agolibrlibname() handles file names containing multiple dots
Frequently asked questions
What is the difference between hubEvals and libr?
Both compete on the same themes — r-package — within Analytics. hubEvals and libr are shipping at a similar cadence (velocity 2.5 vs 2.5, 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 hubEvals better than libr?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. hubEvals and libr are shipping at a similar cadence (velocity 2.5 vs 2.5, 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 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 libr?
Top libr alternatives in Analytics are ranked by recent ship velocity. Browse the "libr alternatives" section above for the current picks, or visit /alternatives/libr for the full list with editorial commentary on each.