HydroPortailStats
France's national flood statistics, ported out of Fortran and into R.
A side-by-side editorial comparison of daedalus and offsetreg — release velocity, themes, recent moves, and the top alternatives to consider.
An epidemic-economic model teaching its interventions to react to the outbreak itself.
daedalus couples an infectious-disease model to sector-level economic costs, letting users test non-pharmaceutical interventions against both epidemic and fiscal outcomes. Over autumn 2025 the intervention layer went from a single fixed closure to sequential timed NPIs and then to closures that lift in response to the model's own instantaneous reproduction number. Alongside that, the cost functions were reworked so illness states map more carefully onto lost productivity.
The parsnip extension for exposure models grew from one algorithm to three
offsetreg supplies parsnip model specifications for regressions with offsets, the form actuarial and epidemiological work needs when modelling rates over exposure. It launched with a single specification, poisson_reg_offset(), backed by glm and glmnet engines. Version 1.1.0 added two more model types - boost_tree_offset() for boosted trees via xgboost and decision_tree_exposure() for weighted decision trees via rpart - and 1.2.0 has been consolidation: argument passthrough to the underlying glm and glmnet calls, an xgboost 3.0 minimum with API accommodation, and cli-formatted messages.
daedalus couples an infectious-disease model to sector-level economic costs, letting users test non-pharmaceutical interventions against both epidemic and fiscal outcomes. Over autumn 2025 the intervention layer went from a single fixed closure to sequential timed NPIs and then to closures that lift in response to the model's own instantaneous reproduction number. Alongside that, the cost functions were reworked so illness states map more carefully onto lost productivity.
The arc is toward a model that behaves like a policy simulator rather than a scenario calculator: interventions now have their own state machine, R_t is computed inside the ODE system, and event handling has been pulled out of the output object. Correction releases sit between the feature ones, including an indexing fix the maintainers flag as required for accurate projections. The versioning is patch-level but the changes are structural.
With R_t and the next-generation matrix now available in-model, the likely next step is richer response rules keyed to those quantities; the entries give no signal on when a stable 1.0 arrives.
offsetreg supplies parsnip model specifications for regressions with offsets, the form actuarial and epidemiological work needs when modelling rates over exposure. It launched with a single specification, poisson_reg_offset(), backed by glm and glmnet engines. Version 1.1.0 added two more model types - boost_tree_offset() for boosted trees via xgboost and decision_tree_exposure() for weighted decision trees via rpart - and 1.2.0 has been consolidation: argument passthrough to the underlying glm and glmnet calls, an xgboost 3.0 minimum with API accommodation, and cli-formatted messages.
The package is following the tidymodels extension playbook: establish one model type, then add types rather than engines, and keep pace with parsnip's own releases. Each version has also tightened the guardrails around correct use - a vignette on when offsetreg should and should not be used, check_args() methods on the specifications - which suggests the maintainer is fielding misapplication rather than feature requests.
Expect additional engines under the existing model types, or a fourth specification, before any change to the offset handling itself, since the package's structure invites extension at the engine layer.
Other Infra & APIs 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 daedalus or offsetreg.
France's national flood statistics, ported out of Fortran and into R.
Sign, zero and narrative restrictions brought into the bsvars ecosystem.
Fast design-based estimators for experiments, coasting on CRAN patches.
The grammar of uncertainty visualization, now drawing the uncertainty in its own estimates.
IP address vectors for R that hit 1.0 and then went quiet.
A column-key toolkit for stitching decades of ecological field data into one table.
See all daedalus alternatives → · See all offsetreg alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. daedalus and offsetreg 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.
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. daedalus and offsetreg 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 Infra & APIs products to evaluate alongside.
Top daedalus alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "daedalus alternatives" section above for the current picks, or visit /alternatives/daedalus for the full list with editorial commentary on each.
Top offsetreg alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "offsetreg alternatives" section above for the current picks, or visit /alternatives/offsetreg for the full list with editorial commentary on each.