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A side-by-side editorial comparison of epiworldR and spmodel — release velocity, themes, recent moves, and the top alternatives to consider.
epiworldR is a thin R shell whose releases track the C++ simulator underneath it
Almost every release here is a version bump of the underlying epiworld C++ library, wrapped and pushed to CRAN. The substantive R-side work is narrow and consistent: exposing simulation outputs that were already computed but not reachable from R — outbreak size, active cases, hospitalizations and their savers. The newest release addresses an AddressSanitizer finding, which is the kind of thing CRAN checks surface on a compiled package.
Spatial regression in R, adding block kriging and then tuning the numerics underneath it
spmodel fits spatial linear and generalised linear models, for both point-referenced and areal data, with prediction and diagnostics attached. Block prediction arrived in 0.11.0 and the releases since have refined it. The most recent release changes optimiser behaviour: the default Nelder-Mead relative stopping tolerance tightens from 1e-4 to 1e-6 to reduce convergence on local rather than global maxima.
Almost every release here is a version bump of the underlying epiworld C++ library, wrapped and pushed to CRAN. The substantive R-side work is narrow and consistent: exposing simulation outputs that were already computed but not reachable from R — outbreak size, active cases, hospitalizations and their savers. The newest release addresses an AddressSanitizer finding, which is the kind of thing CRAN checks surface on a compiled package.
The R package's job is staying current with the simulator and satisfying CRAN, not evolving its own interface. What direction it has shows in which model outputs get exposed next, and in a steady tidy-up of the build — the custom configure script was dropped in favour of R's built-in C++17 and OpenMP settings, and test coverage has been filled in across several releases with automated assistance.
Expect the next release to track another epiworld version bump, with any R-side addition most likely being one more exposed metric or saver, following the pattern of get_hospitalizations and get_outbreak_size.
spmodel fits spatial linear and generalised linear models, for both point-referenced and areal data, with prediction and diagnostics attached. Block prediction arrived in 0.11.0 and the releases since have refined it. The most recent release changes optimiser behaviour: the default Nelder-Mead relative stopping tolerance tightens from 1e-4 to 1e-6 to reduce convergence on local rather than global maxima.
Two threads run in parallel. The first is expanding what can be predicted — point predictions, then areal averages over a region via block kriging, then better accuracy and efficiency for that path as the block size default moved from 1000 to 4000 in 0.12.0. The second is numerical trustworthiness, and it is unusually prominent here: a range-constraint option for stability in 0.9.0, a corrected log determinant of the fixed effects in the restricted log likelihood in 0.11.0, a cloud semivariogram that had been doubling the semivariance fixed in 0.11.1, and now a tighter optimiser tolerance. Several of these silently changed results before they were caught.
Expect the maintainers to keep publishing explicit reproduction instructions alongside numerical default changes, as 0.13.0 does by documenting the `control = list(reltol = 1e-4)` escape hatch. The entries give no signal of expansion beyond the current model families.
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 epiworldR or spmodel.
Chord's assistant can now write to the team's knowledge base, not just read from it.
tidytransit tracks the GTFS spec as it grows, one reader and one router feature at a time.
A tiny grid renderer for oblique-projection cubes, complete since its first release.
BioCro swapped an unstable iteration for real root finders, changing what its crop models compute.
redist keeps rewriting the sampler underneath a district-drawing API it has held stable since 4.0.
epiflows has shipped four releases in eight years, none of which changed the code.
See all epiworldR alternatives → · See all spmodel alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-package — within Analytics. epiworldR and spmodel 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. epiworldR and spmodel 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 epiworldR alternatives in Analytics are ranked by recent ship velocity. Browse the "epiworldR alternatives" section above for the current picks, or visit /alternatives/epiworldr for the full list with editorial commentary on each.
Top spmodel alternatives in Analytics are ranked by recent ship velocity. Browse the "spmodel alternatives" section above for the current picks, or visit /alternatives/spmodel for the full list with editorial commentary on each.