metatools
SDTM supplemental-qualifier merging got sturdier, then the package went quiet for two years.
Comparison · Analytics
cfr vs xplainfi
A side-by-side editorial comparison of cfr and xplainfi — release velocity, themes, recent moves, and the top alternatives to consider.
cfr vs xplainfi: at a glance
What is cfr?
cfr packaged delay-corrected severity estimation, then went quiet on maintenance.
The package estimates disease severity and case ascertainment while correcting for the delay between a case being reported and its outcome being known. After the 0.1.1 rework of the estimation internals and a maintainer handover to Adam Kucharski, activity dropped to a vignette and an R-devel compatibility patch in February 2025.
What is xplainfi?
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.
cfr vs xplainfi: editorial side-by-side
cfr
0.0ANALYTICS
cfr packaged delay-corrected severity estimation, then went quiet on maintenance.
◆ Current state
The package estimates disease severity and case ascertainment while correcting for the delay between a case being reported and its outcome being known. After the 0.1.1 rework of the estimation internals and a maintainer handover to Adam Kucharski, activity dropped to a vignette and an R-devel compatibility patch in February 2025.
◆ Where it's heading
The methodological work is done and consolidated: likelihood approximation is now selected automatically from outbreak size and an initial severity estimate, and the internals were renamed with a dot prefix to close the public surface down to cfr_static(), cfr_rolling() and the data-preparation generic. Releases since have been documentation and compatibility only.
◆ Prediction
The 0.1.0 notes flagged time-varying ascertainment as future work and it has not appeared in the two releases since; nothing in these entries indicates when or whether it lands.
xplainfi
2.5ANALYTICS
xplainfi treats feature importance as an estimate with error bars, not a number.
◆ Current state
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.
◆ Where it's heading
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.
◆ Prediction
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.
Alternatives to cfr and xplainfi
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 cfr or xplainfi.
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logrx
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lobstr
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GSODR
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giscoR
giscoR's 1.0 moved its dataset index into the cache, so new Eurostat releases arrive without a package update.
See all cfr alternatives → · See all xplainfi alternatives →
Recent activity from cfr and xplainfi
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 20d agoxplainfiRefits parallelise; repeated refits deprioritised in favour of resampling
- 5mo agoxplainfiPre-trained learners supported; distribution-free inference added
- 6mo agoxplainfiVersion bumped to mark the package as released
- 9mo agoxplainfiConfidence intervals arrive for feature importance scores
- 1y agocfrR-devel difftime patch and an individual-data vignette
- 2y agocfrSeverity estimator picks its own likelihood approximation
- 2y agocfrDelay-corrected severity and ascertainment estimation on CRAN ⚡
Frequently asked questions
What is the difference between cfr and xplainfi?
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.
Is cfr better than xplainfi?
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.
What are the best alternatives to cfr?
Top cfr alternatives in Analytics are ranked by recent ship velocity. Browse the "cfr alternatives" section above for the current picks, or visit /alternatives/cfr for the full list with editorial commentary on each.
What are the best alternatives to xplainfi?
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.