r2rtf
The clinical-report table engine learned Chinese, then learned to leave RTF entirely
Comparison · Analytics
bundle vs poissonreg
A side-by-side editorial comparison of bundle and poissonreg — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:tidymodels
bundle vs poissonreg: at a glance
What is bundle?
Four releases in three years, each one teaching the serializer about a model type it couldn't carry
bundle solves a narrow, real problem: many R model objects hold pointers to external state — compiled boosters, Java handles, torch tensors — that do not survive being saved and reloaded in another session. It wraps them so they do. The package has shipped four releases since 2022, and the shape of each is the same: extend coverage to another model class, or repair coverage that an upstream release broke.
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.
bundle vs poissonreg: editorial side-by-side
bundle
0.0ANALYTICS
Four releases in three years, each one teaching the serializer about a model type it couldn't carry
◆ Current state
bundle solves a narrow, real problem: many R model objects hold pointers to external state — compiled boosters, Java handles, torch tensors — that do not survive being saved and reloaded in another session. It wraps them so they do. The package has shipped four releases since 2022, and the shape of each is the same: extend coverage to another model class, or repair coverage that an upstream release broke.
◆ Where it's heading
Coverage is the product, so the release cadence is set by the ecosystem rather than by a roadmap. dbarts arrived in 0.1.2, along with extra work to preserve xgboost's nfeatures and feature_names through a round trip; 0.1.3 exists because xgboost changed its model format again. The 0.1.1 fix — recipes steps nested inside workflows — points at the same underlying issue one level up, where the object needing bundling is buried inside a tidymodels pipeline rather than passed directly.
◆ Prediction
Expect the next release to follow the same trigger: either a new parsnip engine that carries external pointers, or another upstream format change in one of the engines already covered. xgboost has now forced two of the four releases.
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.
Alternatives to bundle and poissonreg
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 bundle or poissonreg.
DoseFinding
New stewardship at openpharma, then two releases adding the methods MCP-Mod was missing
webmockr
The stubbing library added httr2 support, then spent a year cutting itself free of everything else
crul
crul took mocking back from webmockr and made it a property of the client itself
dendroNetwork
Six releases, six identical bodies — the feed carries the package abstract instead of release notes
chattr
chattr deleted every LLM integration it had written and outsourced the lot to ellmer
See all bundle alternatives → · See all poissonreg alternatives →
Recent activity from bundle and poissonreg
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 3mo agopoissonregglmnet predictions now default to mean counts
- 8mo agobundlexgboost bundling updated for newer model versions
- 1y agobundledbarts BART models become bundleable
- 2y agobundleRecipes steps inside workflows now bundle correctly
- 3y agobundleFirst CRAN release
- 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 bundle and poissonreg?
Both compete on the same themes — tidymodels — within Analytics. bundle and poissonreg are shipping at a similar cadence (velocity 0.0 vs 0.0, 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 bundle better than poissonreg?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. bundle and poissonreg are shipping at a similar cadence (velocity 0.0 vs 0.0, 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 bundle?
Top bundle alternatives in Analytics are ranked by recent ship velocity. Browse the "bundle alternatives" section above for the current picks, or visit /alternatives/bundle for the full list with editorial commentary on each.
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.