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rjdqa vs spatstat.random

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

Shared themes:r-package

rjdqa vs spatstat.random: at a glance

Featurerjdqaspatstat.random
SectorAnalyticsAnalytics
Velocity score0.02.5
Sparks · 30d00
Top themesofficial-statistics, seasonal-adjustment, quality-assurance, r-packagespatial-statistics, point-processes, simulation, r-package
Last editorial update1h ago9h ago
WebsiteVisit →Visit →

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 →

What is spatstat.random?

spatstat's simulation engine pushes point process generation into three dimensions

spatstat.random generates random point patterns and simulates point process models for the spatstat family. Its recent releases have moved along two lines at once: filling out three-dimensional simulation, and adding conditional simulation to the established cluster process generators. 3.5-1 is a narrow follow-up adding a random Dirichlet-Voronoi tessellation without edge effects.

Read the full spatstat.random trajectory →

rjdqa vs spatstat.random: editorial side-by-side

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.

S2.5

spatstat's simulation engine pushes point process generation into three dimensions

◆ Current state

spatstat.random generates random point patterns and simulates point process models for the spatstat family. Its recent releases have moved along two lines at once: filling out three-dimensional simulation, and adding conditional simulation to the established cluster process generators. 3.5-1 is a narrow follow-up adding a random Dirichlet-Voronoi tessellation without edge effects.

◆ Where it's heading

The clearest arc is dimensional. 3.5-0 carried inhomogeneous Poisson processes, non-uniform random points and Simple Sequential Inhibition into 3D in a single release, and the sibling geometry package followed two months later with more capabilities for three-dimensional point patterns. Alongside that, the generators have been gaining theoretical range — Gaussian random fields in 3.4-4, a new class of theoretical cluster process models and random diffusion in 3.5-0 — while earlier releases concentrated on conditional simulation and efficiency in the existing 2D routines.

◆ Prediction

Expect the 3D work to continue propagating into the model-fitting and geometry packages before spatstat.random adds another dimension-independent generator, since the 3D features here have already begun appearing downstream. The entries do not indicate which estimator gets 3D support next.

Alternatives to rjdqa and spatstat.random

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 rjdqa or spatstat.random.

See all rjdqa alternatives → · See all spatstat.random alternatives →

Recent activity from rjdqa and spatstat.random

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

  1. 20d agospatstat.randomEdge-effect-free random Dirichlet-Voronoi tessellation
  2. 2mo agospatstat.randomThree-dimensional point process simulation arrives
  3. 6mo agospatstat.randomGaussian random field generation added
  4. 9mo agorjdqaForecast observations and conditional trading-days test in dashboards
  5. 10mo agospatstat.randomrunifdisc efficiency and fixed-count simulation options
  6. 1y agospatstat.randomConditional simulation for the cluster process generators
  7. 1y agospatstat.randomFaster rpoispp for tessellation-defined intensity
  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 rjdqa and spatstat.random?

Both compete on the same themes — r-package — within Analytics. spatstat.random is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.

Is rjdqa better than spatstat.random?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. spatstat.random is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.

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.

What are the best alternatives to spatstat.random?

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