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Comparison · Analytics

EpiNow2 vs rjdqa

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

Shared themes:r-package

EpiNow2 vs rjdqa: at a glance

FeatureEpiNow2rjdqa
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesepidemiology, bayesian-modelling, reproduction-number, r-packageofficial-statistics, seasonal-adjustment, quality-assurance, r-package
Last editorial update9h 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 rjdqa?

rjdqa keeps refining one screen: the seasonal adjustment quality dashboard

rjdqa builds quality assessment dashboards for seasonal adjustment models produced by JDemetra+, aimed at official statisticians reviewing adjusted series. Essentially all development goes into two functions, simple_dashboard() and its denser variant simple_dashboard2(). Version 0.1.6 adds parameters to append observations to the forecast and to control whether the residual trading-days test is printed, defaulting to monthly series only, plus outlier table layout work and user-defined calendar regressor support in sc_dashboard().

Read the full rjdqa trajectory →

EpiNow2 vs rjdqa: 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
rjdqa
ANALYTICS
0.0

rjdqa keeps refining one screen: the seasonal adjustment quality dashboard

◆ Current state

rjdqa builds quality assessment dashboards for seasonal adjustment models produced by JDemetra+, aimed at official statisticians reviewing adjusted series. Essentially all development goes into two functions, simple_dashboard() and its denser variant simple_dashboard2(). Version 0.1.6 adds parameters to append observations to the forecast and to control whether the residual trading-days test is printed, defaulting to monthly series only, plus outlier table layout work and user-defined calendar regressor support in sc_dashboard().

◆ Where it's heading

The package has converged on a single deliverable and is tuning it against reviewer practice. Each release adds a parameter that lets the analyst include or exclude one element of the dashboard, or adjusts how densely information is packed into the fixed space of the layout. The td_effect default — print the test only for monthly series — is characteristic: the knowledge about when a diagnostic is meaningful is being encoded into the tool rather than left to the reader.

◆ Prediction

The pattern of adding one toggle per diagnostic per release points at the same thing again, most likely another test given a conditional default, rather than a new dashboard function alongside the two that exist.

Alternatives to EpiNow2 and rjdqa

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 rjdqa.

See all EpiNow2 alternatives → · See all rjdqa alternatives →

Recent activity from EpiNow2 and rjdqa

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

  1. 1mo agoEpiNow2estimate_truncation gains full delay and observation options
  2. 6mo agoEpiNow2Unified return objects and shared accessors across all models
  3. 9mo agorjdqaForecast observations and conditional trading-days test in dashboards
  4. 1y agoEpiNow2Patch for an upstream rstan issue
  5. 1y agoEpiNow2Accumulation for irregularly reported data; unified priors
  6. 1y agoEpiNow2Matern kernel spectral density fix and GP prior revert
  7. 1y agoEpiNow2Gaussian Process model improvements and explicit defaults
  8. 1y agorjdqaFix tail() usage on ts objects
  9. 2y agorjdqaFix dependency minimums and outlier ordering
  10. 2y agorjdqasimple_dashboard2() added; deprecated sa_dashboard() removed
  11. 2y agorjdqasimple_dashboard() introduced; sa_dashboard() deprecated
  12. 7y agorjdqaFirst CRAN release

Frequently asked questions

What is the difference between EpiNow2 and rjdqa?

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

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

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