osmapiR
osmapiR is the rare API client that tracks its server's wiki revision numbers in the changelog.
Comparison · Analytics
poissonreg vs waywiser
A side-by-side editorial comparison of poissonreg and waywiser — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:tidymodels
poissonreg vs waywiser: 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 waywiser?
Spatial model assessment that spent the last year on cross-platform arithmetic and CRAN rules.
waywiser provides spatial model assessment metrics in a tidymodels idiom — spatial autocorrelation measures, area of applicability, and multi-scale assessment of predictions. The substantive work landed in 0.3.0 through 0.5.0, and the recent releases are consolidation: 0.6.0 made metric functions return NA everywhere they previously returned NaN, because macOS disagreed with every other platform, and taught ww_multi_scale() to handle classification and class probability metrics correctly when given rasters. The three releases since are entirely CRAN policy compliance — no internet downloads during checks, no writing to directories, no syntax that would raise the R version floor.
poissonreg vs waywiser: 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.
waywiser
0.0ANALYTICS
Spatial model assessment that spent the last year on cross-platform arithmetic and CRAN rules.
◆ Current state
waywiser provides spatial model assessment metrics in a tidymodels idiom — spatial autocorrelation measures, area of applicability, and multi-scale assessment of predictions. The substantive work landed in 0.3.0 through 0.5.0, and the recent releases are consolidation: 0.6.0 made metric functions return NA everywhere they previously returned NaN, because macOS disagreed with every other platform, and taught ww_multi_scale() to handle classification and class probability metrics correctly when given rasters. The three releases since are entirely CRAN policy compliance — no internet downloads during checks, no writing to directories, no syntax that would raise the R version floor.
◆ Where it's heading
The package has reached the point where the interesting bugs are cross-platform and cross-package rather than statistical. Its main function, ww_multi_scale(), has been the focus of nearly every release since 0.4.0, working through units handling, aggregation ordering, raster inputs and metric-type dispatch. The dependency on vip and the tidymodels metric machinery means a share of releases exist only to track breaking changes elsewhere.
◆ Prediction
Expect the next substantive release to continue on ww_multi_scale() edge cases, given that it has absorbed most of the fixes in this window. The recent run of CRAN-compliance patches suggests no feature work is currently in flight.
Alternatives to poissonreg and waywiser
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 waywiser.
ymlthis
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forestly
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pharmaverseadam
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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 waywiser alternatives →
Recent activity from poissonreg and waywiser
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 3mo agopoissonregglmnet predictions now default to mean counts
- 1y agowaywiserStops downloading data during CRAN checks
- 1y agowaywiserVignettes no longer write to CRAN directories
- 1y agowaywiserKeeps the R version floor below 4.1
- 2y agowaywiserNaN results become NA; raster metrics dispatch correctly
- 2y agowaywiserGuards against ignored grid arguments; faster on sf data
- 2y agowaywiserFixes wrong observation counts and ignored grid units
- 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 waywiser?
Both compete on the same themes — tidymodels — within Analytics. poissonreg and waywiser 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 poissonreg better than waywiser?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. poissonreg and waywiser 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 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 waywiser?
Top waywiser alternatives in Analytics are ranked by recent ship velocity. Browse the "waywiser alternatives" section above for the current picks, or visit /alternatives/waywiser for the full list with editorial commentary on each.