tern.rbmi
Reference-based multiple imputation tables, shipping only what CRAN checks demand.
A side-by-side editorial comparison of CMAQ and EpiNow2 — release velocity, themes, recent moves, and the top alternatives to consider.
CMAQ went global in v5.5, and has been patching that surface ever since.
CMAQ is the EPA's Community Multiscale Air Quality modeling system, used for regulatory and research air quality simulation. Its release rhythm is strictly two-tier: numbered major versions carry new science and fresh benchmark datasets, while the x.y.z.n updates carry bug fixes against documentation and benchmarks that stay pinned to the parent version. The current line is v5.5, which introduced CRACMM2 chemistry and coupling to MPAS-A meteorology, followed by three patch rollups.
EpiNow2 unified its model interface, then went back to deepen the estimators behind it
EpiNow2 estimates reproduction numbers, infections and delay distributions from incomplete epidemiological reporting data. 1.8.0 was the structural turning point: every main modelling function now returns a consistent S3 object with `fit`, `args` and `observations`, reachable through shared accessors. The releases either side of it work on estimator quality — accumulation of irregularly reported data in 1.7.0, and a substantial expansion of `estimate_truncation()` in 1.9.0.
CMAQ is the EPA's Community Multiscale Air Quality modeling system, used for regulatory and research air quality simulation. Its release rhythm is strictly two-tier: numbered major versions carry new science and fresh benchmark datasets, while the x.y.z.n updates carry bug fixes against documentation and benchmarks that stay pinned to the parent version. The current line is v5.5, which introduced CRACMM2 chemistry and coupling to MPAS-A meteorology, followed by three patch rollups.
The v5.5 patches cluster around the newest and most sensitive components. ISAM source apportionment and DDM-3D sensitivity analysis account for corrections in every one of the three updates, and CRACMM2 needed fixes within months of release. That is the expected shape after a major version lands: the science is stable, the instrumentation built on top of it is not. Parallel I/O work in the latest patch suggests the global configurations are now being run at scales that expose throughput limits.
The next major version will fold these fixes in with new science, documentation and benchmark data — the release notes state this explicitly each time. Until then, expect further ISAM and DDM-3D corrections, which have appeared in every patch so far.
EpiNow2 estimates reproduction numbers, infections and delay distributions from incomplete epidemiological reporting data. 1.8.0 was the structural turning point: every main modelling function now returns a consistent S3 object with `fit`, `args` and `observations`, reachable through shared accessors. The releases either side of it work on estimator quality — accumulation of irregularly reported data in 1.7.0, and a substantial expansion of `estimate_truncation()` in 1.9.0.
The package spent this window paying down interface debt and is now extending from the tidier base. Options that existed only for `estimate_infections()` have been propagated outward: `estimate_truncation()` gained the full `dist_spec` delay families, `obs_opts()` observation model selection between Poisson and negative binomial, and the `likelihood` and `return_likelihood` settings that make prior-only fits and loo-compatible output possible. Hardcoded assumptions are being replaced by specifiable ones in the same motion — the truncation model's additive noise term was a fixed `sigma ~ normal(0, 1)` prior and is now a `dist_spec` argument.
Expect the remaining modelling functions to keep converging on the shared options interface, since the last two releases have each moved another function onto it. A new `estimate_dist()` for interval-censored linelist data suggests delay estimation is the area still gaining surface.
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 CMAQ or EpiNow2.
Reference-based multiple imputation tables, shipping only what CRAN checks demand.
An MMRM tabulation package that has published nothing since its 2024 CRAN releases.
A single-purpose ggplot2 inset tool, refining the same three arguments.
An R symbolic-maths binding whose changelog is really the C++ core's release notes.
gtfstools stopped guarding its own object model and started accepting everyone else's.
The glue package that makes R carry units and uncertainty through the same calculation.
See all CMAQ alternatives → · See all EpiNow2 alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. CMAQ and EpiNow2 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. CMAQ and EpiNow2 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.
Top CMAQ alternatives in Analytics are ranked by recent ship velocity. Browse the "CMAQ alternatives" section above for the current picks, or visit /alternatives/cmaq for the full list with editorial commentary on each.
Top EpiNow2 alternatives in Analytics are ranked by recent ship velocity. Browse the "EpiNow2 alternatives" section above for the current picks, or visit /alternatives/epinow2 for the full list with editorial commentary on each.