paleobuddy
paleobuddy can now simulate trait-dependent diversification, not just birth-death.
A side-by-side editorial comparison of epikit and EpiNow2 — release velocity, themes, recent moves, and the top alternatives to consider.
epikit narrows to field-epidemiology helpers, handing proportions to a sibling package
epikit is a set of small helpers for applied epidemiology in R — age categorisation, date reconstruction from partial records, and related field-data chores, developed in the R4Epis orbit. Version 0.2.0 moved the proportion functions out to epitabulate, improved how find_date_cause(), find_start_date() and find_end_date() handle dates falling outside the period, and added a floor argument to age_categories() so the lowest band reads as under one rather than zero to zero.
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.
epikit is a set of small helpers for applied epidemiology in R — age categorisation, date reconstruction from partial records, and related field-data chores, developed in the R4Epis orbit. Version 0.2.0 moved the proportion functions out to epitabulate, improved how find_date_cause(), find_start_date() and find_end_date() handle dates falling outside the period, and added a floor argument to age_categories() so the lowest band reads as under one rather than zero to zero.
The package is being scoped down rather than built out. The 0.1.3 restructuring and the 0.2.0 handover of proportions to epitabulate are the same move made twice: push functionality into the package where it belongs and keep epikit to the toolkit that field epidemiologists reach for directly. The rest of the history is dependency compatibility work against dplyr and tibble.
With proportions gone and dependencies trimmed, the remaining functions cluster tightly around dates and age bands, so further refinement of the date-reconstruction helpers is more likely than new capability areas.
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 epikit or EpiNow2.
paleobuddy can now simulate trait-dependent diversification, not just birth-death.
geodist stays dependency-free and fast, and warns you when 'cheap' distances stop being honest.
errors keeps making uncertainty print the way each scientific field expects.
CMAQ went global in v5.5, and has been patching that surface ever since.
enpls has not changed its statistics since 2016 — only its website, twice.
grex is a lookup table with a version number — it ships when the annotation moves.
See all epikit alternatives → · See all EpiNow2 alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — epidemiology, r-package — within Analytics. epikit 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. epikit 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 epikit alternatives in Analytics are ranked by recent ship velocity. Browse the "epikit alternatives" section above for the current picks, or visit /alternatives/epikit-r 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.