metatools
SDTM supplemental-qualifier merging got sturdier, then the package went quiet for two years.
A side-by-side editorial comparison of tern.rbmi and xplainfi — release velocity, themes, recent moves, and the top alternatives to consider.
Reference-based multiple imputation tables, shipping only what CRAN checks demand.
tern.rbmi renders the output of {rbmi} reference-based multiple imputation analyses into tern tables for clinical reporting. Its three most recent releases exist to satisfy CRAN: restricting vignette builds to gcc, adding V8 to Suggests, and a plain resubmission. No user-facing functionality has changed in the visible window.
xplainfi treats feature importance as an estimate with error bars, not a number.
xplainfi implements feature importance methods for mlr3 — perturbation-based PFI, CFI and RFI, refit-based LOCO and WVIM, and SAGE. Its defining choice is that importance scores come with inference attached: several confidence-interval methods, including the Nadeau-Bengio correction and a distribution-free option added in 1.1.0. It declared itself released at 1.0.0 in January 2026.
tern.rbmi renders the output of {rbmi} reference-based multiple imputation analyses into tern tables for clinical reporting. Its three most recent releases exist to satisfy CRAN: restricting vignette builds to gcc, adding V8 to Suggests, and a plain resubmission. No user-facing functionality has changed in the visible window.
This is a thin adapter package and behaves like one — it moves when CRAN or an upstream dependency forces it to. Between 2022 and 2024 the feed shows only version bumps, and the 2025 releases are packaging concerns rather than analysis changes.
Expect the next release to be triggered by a CRAN check failure or an {rbmi} update rather than by new tabulation features.
xplainfi implements feature importance methods for mlr3 — perturbation-based PFI, CFI and RFI, refit-based LOCO and WVIM, and SAGE. Its defining choice is that importance scores come with inference attached: several confidence-interval methods, including the Nadeau-Bengio correction and a distribution-free option added in 1.1.0. It declared itself released at 1.0.0 in January 2026.
Two lines of work run in parallel. The statistical side keeps adding inference options — variance corrections, conditional predictive impact, and the Lei et al. observation-wise loss-difference test — while the computational side attacks the cost of refit-based methods, most recently with a batch_size argument that parallelises refits and a default of one refit per resampling iteration. Support for pre-trained learners in 1.1.0 removes the refit requirement entirely in some workflows.
The stated reasoning that budget is better spent on resampling iterations than repeated refits suggests n_repeats may be removed from WVIM and LOCO outright, as the release notes hint.
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 tern.rbmi or xplainfi.
SDTM supplemental-qualifier merging got sturdier, then the package went quiet for two years.
marquee is filling in the typographic details — outlines, border types, real font metrics for underlines.
A clinical-script logger that stopped shipping after its 0.2 line, changelogs made of merged PRs.
R's object inspector is losing its view of the internals as CRAN closes off the private C API.
A weather-station data client that broke one return type to hand back distances instead of bare IDs.
giscoR's 1.0 moved its dataset index into the cache, so new Eurostat releases arrive without a package update.
See all tern.rbmi alternatives → · See all xplainfi alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. xplainfi 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. xplainfi 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.
Top tern.rbmi alternatives in Analytics are ranked by recent ship velocity. Browse the "tern.rbmi alternatives" section above for the current picks, or visit /alternatives/tern-rbmi for the full list with editorial commentary on each.
Top xplainfi alternatives in Analytics are ranked by recent ship velocity. Browse the "xplainfi alternatives" section above for the current picks, or visit /alternatives/xplainfi for the full list with editorial commentary on each.