osmapiR
osmapiR is the rare API client that tracks its server's wiki revision numbers in the changelog.
Comparison · Analytics
poissonreg vs xplainfi
A side-by-side editorial comparison of poissonreg and xplainfi — release velocity, themes, recent moves, and the top alternatives to consider.
poissonreg vs xplainfi: at a glance
What is poissonreg?
poissonreg gave its models away to parsnip and kept the glue — now it just keeps glmnet honest.
poissonreg is a tidymodels extension that wires Poisson and zero-inflated count regression into the parsnip interface. Its defining event was giving up ownership: the model definition functions moved into parsnip itself, leaving this package as engine bindings and prediction plumbing. The current dev release is entirely correctness and hygiene work — glmnet predictions now default to mean counts rather than the linear predictor, and single-observation prediction works at last.
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.
poissonreg vs xplainfi: editorial side-by-side
poissonreg
0.0ANALYTICS
poissonreg gave its models away to parsnip and kept the glue — now it just keeps glmnet honest.
◆ Current state
poissonreg is a tidymodels extension that wires Poisson and zero-inflated count regression into the parsnip interface. Its defining event was giving up ownership: the model definition functions moved into parsnip itself, leaving this package as engine bindings and prediction plumbing. The current dev release is entirely correctness and hygiene work — glmnet predictions now default to mean counts rather than the linear predictor, and single-observation prediction works at last.
◆ Where it's heading
Release cadence has collapsed from yearly to a four-year gap between 1.0.1 and the current development version, and the content has shifted from features to deduplication against parsnip — copied helper functions replaced by the upstream originals, obsolete generic registrations removed, tests migrated to the shared extension-package pattern. This is what a stabilized tidymodels satellite looks like: the interface lives upstream, and the package's job is to not drift from it.
◆ Prediction
The dev version's accumulated fixes point to a CRAN release of 1.0.2 as the next move, with content limited to the glmnet prediction corrections rather than any new engine or model type.
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 poissonreg 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 poissonreg or xplainfi.
ymlthis
ymlthis retired itself, naming Quarto as the reason it no longer needs to exist.
forestly
forestly built an interactive safety review tool, then taught it to produce submission-ready RTF.
pharmaverseadam
pharmaverseadam is the pharmaverse's test-data mirror, and it now covers neurology.
pkglite
pkglite's whole job is knowing which files in an R package are text — and it keeps getting better at guessing.
gMCPLite
gMCPLite exists to be gMCP without Java, and its releases guard that boundary rather than extend it.
See all poissonreg alternatives → · See all xplainfi alternatives →
Recent activity from poissonreg and xplainfi
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 21d agoxplainfiRefits parallelise; repeated refits deprioritised in favour of resampling
- 3mo agopoissonregglmnet predictions now default to mean counts
- 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
- 3y agopoissonregDocumentation regenerated for valid HTML5
- 4y agopoissonregCase weight support tracks parsnip 1.0.0
- 4y agopoissonregModel definitions move out of poissonreg into parsnip ⚡
- 4y agopoissonregglm becomes the default engine; tidy() for hurdle models
- 5y agopoissonregFirst release, with a glmnet column-order safeguard
Frequently asked questions
What is the difference between poissonreg 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 poissonreg 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 poissonreg?
Top poissonreg alternatives in Analytics are ranked by recent ship velocity. Browse the "poissonreg alternatives" section above for the current picks, or visit /alternatives/poissonreg 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.