rjd3highfreq
rjd3highfreq ships whatever the Java side ships, and only occasionally says what that was.
Comparison · Analytics
EpiNow2 vs ggstatsplot
A side-by-side editorial comparison of EpiNow2 and ggstatsplot — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-package
EpiNow2 vs ggstatsplot: at a glance
What is EpiNow2?
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.
What is ggstatsplot?
ggstatsplot reached 1.0 by adding tests, having outsourced its statistics years ago.
ggstatsplot produces ggplot2 graphics with statistical test results embedded in the subtitle and caption — comparisons, correlations, contingency tables, histograms. Since the 2019 refactoring that moved all statistical computation into the separate statsExpressions package, its own release notes have been dominated by upstream tracking: adapting to ggplot2, dplyr, purrr and easystats changes. The 1.0.0 release in April 2026 breaks that run with real additions to the contingency-table functions.
EpiNow2 vs ggstatsplot: editorial side-by-side
EpiNow2
0.0ANALYTICS
EpiNow2 unified its model interface, then went back to deepen the estimators behind it
◆ Current state
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.
◆ Where it's heading
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.
◆ Prediction
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.
ggstatsplot
0.0ANALYTICS
ggstatsplot reached 1.0 by adding tests, having outsourced its statistics years ago.
◆ Current state
ggstatsplot produces ggplot2 graphics with statistical test results embedded in the subtitle and caption — comparisons, correlations, contingency tables, histograms. Since the 2019 refactoring that moved all statistical computation into the separate statsExpressions package, its own release notes have been dominated by upstream tracking: adapting to ggplot2, dplyr, purrr and easystats changes. The 1.0.0 release in April 2026 breaks that run with real additions to the contingency-table functions.
◆ Where it's heading
The architecture explains the cadence. With statistics living in statsExpressions, ggstatsplot's own releases are mostly the tax of sitting on top of a fast-moving plotting and tidyverse stack — five of the six most recent entries change nothing a user would notice. When substantive work does arrive it clusters in the plotting layer's coverage of test families, as in 1.0.0's one-sample goodness-of-fit support and pairwise contingency analyses. The maintainer is also visibly deliberate about scope, having removed the normality-curve overlay in 0.12.4 for being unrelated to the analysis in question.
◆ Prediction
Expect continued parity work across the plot family — features that exist in one function being extended to its siblings, as goodness-of-fit support moved from ggpiestats to ggbarstats — punctuated by maintenance releases tracking ggplot2 and easystats.
Alternatives to EpiNow2 and ggstatsplot
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 EpiNow2 or ggstatsplot.
audubon
audubon's release feed is almost entirely Renovate bumping the JavaScript toolchain behind its Japanese text splitter.
affiner
affiner is quietly turning a grid transformation helper into a small computational geometry library.
ageproR
ageproR spent two years chasing a moving file format, then added the recruitment models that justify the effort.
r-ledger
ledger adds a Rust toolchain fallback, so beancount imports work whether or not the Python tooling is installed.
gridpattern
gridpattern keeps widening its catalogue, and the newest patterns finally use the device's own line rendering.
See all EpiNow2 alternatives → · See all ggstatsplot alternatives →
Recent activity from EpiNow2 and ggstatsplot
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 1mo agoEpiNow2estimate_truncation gains full delay and observation options
- 3mo agoggstatsplotPairwise contingency tests and one-sample goodness-of-fit
- 4mo agoggstatsplotInternal maintenance only
- 6mo agoEpiNow2Unified return objects and shared accessors across all models ⚡
- 6mo agoggstatsplotAdapted to dplyr 1.2.0 and purrr 1.2.1
- 8mo agoggstatsplotContributor list updated in DESCRIPTION
- 10mo agoggstatsplotSecondary axis label parsing fixed in gghistostats
- 11mo agoggstatsplotAdapted to the latest ggplot2 release
- 1y agoEpiNow2Patch for an upstream rstan issue
- 1y agoEpiNow2Accumulation for irregularly reported data; unified priors
- 1y agoEpiNow2Matern kernel spectral density fix and GP prior revert
- 1y agoEpiNow2Gaussian Process model improvements and explicit defaults
Frequently asked questions
What is the difference between EpiNow2 and ggstatsplot?
Both compete on the same themes — r-package — within Analytics. EpiNow2 and ggstatsplot 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 EpiNow2 better than ggstatsplot?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. EpiNow2 and ggstatsplot 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 EpiNow2?
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.
What are the best alternatives to ggstatsplot?
Top ggstatsplot alternatives in Analytics are ranked by recent ship velocity. Browse the "ggstatsplot alternatives" section above for the current picks, or visit /alternatives/ggstatsplot for the full list with editorial commentary on each.