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Comparison · Analytics

epikit vs rjdqa

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

Shared themes:r-package

epikit vs rjdqa: at a glance

Featureepikitrjdqa
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesepidemiology, field-data, date-handling, r-packageofficial-statistics, seasonal-adjustment, quality-assurance, r-package
Last editorial update1h ago1h ago
WebsiteVisit →Visit →

What is epikit?

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.

Read the full epikit 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 →

epikit vs rjdqa: editorial side-by-side

E
epikit
ANALYTICS
0.0

epikit narrows to field-epidemiology helpers, handing proportions to a sibling package

◆ Current state

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.

◆ Where it's heading

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.

◆ Prediction

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.

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 epikit 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 epikit or rjdqa.

See all epikit alternatives → · See all rjdqa alternatives →

Recent activity from epikit and rjdqa

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

  1. 9mo agoepikitProportion functions moved to epitabulate; date helpers warn correctly
  2. 9mo agorjdqaForecast observations and conditional trading-days test in dashboards
  3. 1y agorjdqaFix tail() usage on ts objects
  4. 2y agorjdqaFix dependency minimums and outlier ordering
  5. 2y agorjdqasimple_dashboard2() added; deprecated sa_dashboard() removed
  6. 2y agorjdqasimple_dashboard() introduced; sa_dashboard() deprecated
  7. 3y agoepikitFunctions rearranged across sibling packages
  8. 5y agoepikitRaise dplyr and tibble minimums; move CI to GitHub Actions
  9. 5y agoepikitCompatibility release for dplyr 1.0.0
  10. 6y agoepikitFirst CRAN release
  11. 7y agorjdqaFirst CRAN release

Frequently asked questions

What is the difference between epikit and rjdqa?

Both compete on the same themes — r-package — within Analytics. epikit 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 epikit better than rjdqa?

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

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.

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.