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EpiNow2 vs rjd3highfreq

A side-by-side editorial comparison of EpiNow2 and rjd3highfreq — release velocity, themes, recent moves, and the top alternatives to consider.

Shared themes:r-package

EpiNow2 vs rjd3highfreq: at a glance

FeatureEpiNow2rjd3highfreq
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesepidemiology, bayesian-modelling, reproduction-number, r-packageseasonal-adjustment, time-series, jdemetra, r-package
Last editorial update6h ago1h ago
WebsiteVisit →Visit →

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.

Read the full EpiNow2 trajectory →

What is rjd3highfreq?

rjd3highfreq ships whatever the Java side ships, and only occasionally says what that was.

An R wrapper around JDemetra+ routines for seasonal adjustment of high-frequency time series, built on fractional airline decomposition. Only three releases are on record, roughly one every six months, and two of them describe nothing beyond updated .jar files. The package is a thin binding whose substance lives in the Java libraries it packages, and the release notes reflect that literally.

Read the full rjd3highfreq trajectory →

EpiNow2 vs rjd3highfreq: editorial side-by-side

E
EpiNow2
ANALYTICS
0.0

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.

R
rjd3highfreq
ANALYTICS
0.0

rjd3highfreq ships whatever the Java side ships, and only occasionally says what that was.

◆ Current state

An R wrapper around JDemetra+ routines for seasonal adjustment of high-frequency time series, built on fractional airline decomposition. Only three releases are on record, roughly one every six months, and two of them describe nothing beyond updated .jar files. The package is a thin binding whose substance lives in the Java libraries it packages, and the release notes reflect that literally.

◆ Where it's heading

The one release with detail points at where the work actually is: 2.4.1 exposes eps and deps parameters on fractionalAirlineDecomposition(), controlling the optimisation routine's convergence precision and the step size for its numerical derivatives. That is tuning access for users whose series were not converging well under the defaults, and it is the only user-facing surface change visible here. The earlier entry even appears under a different package name, rjd3xhighfreq, which suggests some instability in how this line is published.

◆ Prediction

Expect further releases tracking JDemetra+ .jar versions, with R-level parameters exposed only as specific estimation problems surface; the entries do not support a firmer read than that.

Alternatives to EpiNow2 and rjd3highfreq

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 rjd3highfreq.

See all EpiNow2 alternatives → · See all rjd3highfreq alternatives →

Recent activity from EpiNow2 and rjd3highfreq

Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.

  1. 1mo agoEpiNow2estimate_truncation gains full delay and observation options
  2. 3mo agorjd3highfreqOptimisation precision and derivative step exposed on airline decomposition
  3. 6mo agoEpiNow2Unified return objects and shared accessors across all models
  4. 8mo agorjd3highfreqrjd3highfreq 2.4.0
  5. 1y agorjd3highfreqrjd3xhighfreq 2.3.0
  6. 1y agoEpiNow2Patch for an upstream rstan issue
  7. 1y agoEpiNow2Accumulation for irregularly reported data; unified priors
  8. 1y agoEpiNow2Matern kernel spectral density fix and GP prior revert
  9. 1y agoEpiNow2Gaussian Process model improvements and explicit defaults

Frequently asked questions

What is the difference between EpiNow2 and rjd3highfreq?

Both compete on the same themes — r-package — within Analytics. EpiNow2 and rjd3highfreq 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 rjd3highfreq?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. EpiNow2 and rjd3highfreq 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 rjd3highfreq?

Top rjd3highfreq alternatives in Analytics are ranked by recent ship velocity. Browse the "rjd3highfreq alternatives" section above for the current picks, or visit /alternatives/rjd3highfreq for the full list with editorial commentary on each.