metatools
SDTM supplemental-qualifier merging got sturdier, then the package went quiet for two years.
Comparison · Analytics
serofoi vs xplainfi
A side-by-side editorial comparison of serofoi and xplainfi — release velocity, themes, recent moves, and the top alternatives to consider.
serofoi vs xplainfi: at a glance
What is serofoi?
serofoi grew a serosurvey simulator alongside the force-of-infection models it was built to fit.
serofoi estimates the force of infection from serological survey data using Bayesian serocatalytic models fitted through Stan. Beyond fitting it now simulates serosurveys — specifying a model and a survey design and generating the data such a survey would produce. The most recent release is visualisation and naming work.
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.
serofoi vs xplainfi: editorial side-by-side
serofoi
0.0ANALYTICS
serofoi grew a serosurvey simulator alongside the force-of-infection models it was built to fit.
◆ Current state
serofoi estimates the force of infection from serological survey data using Bayesian serocatalytic models fitted through Stan. Beyond fitting it now simulates serosurveys — specifying a model and a survey design and generating the data such a survey would produce. The most recent release is visualisation and naming work.
◆ Where it's heading
The package moved from fitting-only to a fit-and-simulate pair. 0.1.0 added simulation from time- or age-varying force-of-infection trends and simplified the fitted object down to a Stan fit; 1.0.2 broadened simulation into full serosurvey generation with its own vignette. 1.0.3 then spent its effort on naming consistency and plotting options, which is what a package does once its scope is set.
◆ Prediction
With simulation and fitting both in place, the natural next step is tooling that closes the loop between them — recovery checks or study-design guidance built on simulated surveys.
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 serofoi 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 serofoi or xplainfi.
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lobstr
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See all serofoi alternatives → · See all xplainfi alternatives →
Recent activity from serofoi 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 agoserofoiConstant FoI plots, r-hat plotting and shorter parameter names
- 1y agoserofoiSerological surveys can now be simulated end to end
- 2y agoserofoiSimulation functions added; fitted output simplified to a Stan fit
- 3y agoserofoiFirst release: three force-of-infection models and the core modules
Frequently asked questions
What is the difference between serofoi 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 serofoi 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 serofoi?
Top serofoi alternatives in Analytics are ranked by recent ship velocity. Browse the "serofoi alternatives" section above for the current picks, or visit /alternatives/serofoi 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.