← Back to home
Comparison · Analytics

gsDesign2 vs tulpa

A side-by-side editorial comparison of gsDesign2 and tulpa — release velocity, themes, recent moves, and the top alternatives to consider.

gsDesign2 vs tulpa: at a glance

FeaturegsDesign2tulpa
SectorAnalyticsAnalytics
Velocity score3.87.5
Sparks · 30d12
Top themesclinical-trials, group-sequential, biostatistics, pharmaversebayesian-inference, cran-release, r-packages, spatial-modeling
Last editorial update5d ago8h ago
WebsiteVisit →Visit →

What is gsDesign2?

Group sequential design tooling that now monitors for harm, not just efficacy and futility.

gsDesign2 is the Merck-authored R package for group sequential clinical trial design under non-proportional hazards, and it has spent the last two years filling in the statistical surface its predecessor gsDesign established. Recent releases added conditional power (gs_cp, gs_cp_npe), sequential p-values, risk-difference designs with minimal risk weighting, and boundary updates from blinded interim estimates. Version 1.2.0 adds harm boundaries across the AHR and NPE design and power functions, wired through every summary and table export path.

Read the full gsDesign2 trajectory →

What is tulpa?

The 0.0.x train stops at CRAN: tulpa's engine ships to the ecosystem it already anchors.

tulpa is the C++/R Bayesian spatial inference engine sitting under gcol33's family of ecological occupancy packages, tagging 0.0.x releases several times a week. 0.1.0 is its first CRAN release, and the notes state outright that the engine surface is unchanged from 0.0.198 — the work is packaging discipline: local T bindings rebound to n_t/n_times, OpenMP teams capped under R CMD check, the pkgdown deploy narrowed, an aspell dictionary added. The window behind it splits between the S3 generics conversion and numerical-correctness work in the nested-Laplace grid.

Read the full tulpa trajectory →

gsDesign2 vs tulpa: editorial side-by-side

G
gsDesign2
ANALYTICS
3.8

Group sequential design tooling that now monitors for harm, not just efficacy and futility.

◆ Current state

gsDesign2 is the Merck-authored R package for group sequential clinical trial design under non-proportional hazards, and it has spent the last two years filling in the statistical surface its predecessor gsDesign established. Recent releases added conditional power (gs_cp, gs_cp_npe), sequential p-values, risk-difference designs with minimal risk weighting, and boundary updates from blinded interim estimates. Version 1.2.0 adds harm boundaries across the AHR and NPE design and power functions, wired through every summary and table export path.

◆ Where it's heading

The package is converging on parity with gsDesign while extending past it — each release either closes a gap against the older package or adds a boundary type gsDesign never had. A visible second track is output plumbing: every new statistical feature now arrives already threaded through summary(), gs_bound_summary(), as_gt(), and as_rtf(), which is what regulatory submission work actually consumes. Performance work is steady but secondary, with gs_design_ahr() roughly 2x faster in 1.1.9.

◆ Prediction

Expect the harm boundary work to propagate into the WLR and risk-difference design families, which are the two design branches 1.2.0 left untouched, along with a vignette bridging harm boundaries to the remaining gsDesign test types.

T
tulpa
ANALYTICS
7.5

The 0.0.x train stops at CRAN: tulpa's engine ships to the ecosystem it already anchors.

◆ Current state

tulpa is the C++/R Bayesian spatial inference engine sitting under gcol33's family of ecological occupancy packages, tagging 0.0.x releases several times a week. 0.1.0 is its first CRAN release, and the notes state outright that the engine surface is unchanged from 0.0.198 — the work is packaging discipline: local T bindings rebound to n_t/n_times, OpenMP teams capped under R CMD check, the pkgdown deploy narrowed, an aspell dictionary added. The window behind it splits between the S3 generics conversion and numerical-correctness work in the nested-Laplace grid.

◆ Where it's heading

Two moves in nine days point at the same destination: the generics conversion made tulpa extensible by downstream packages, and CRAN admission makes it installable by them. The current cadence — several tags a week, some existing only to record a measurement that produced no code change — does not survive CRAN's submission overhead, so the release rhythm has to slow whether or not the project intends it. The correctness work still clusters on the joint nested-Laplace driver, and 0.1.0 extends the same diagnostics habit with .NL_AXIS_SD_REASONS, a closed vocabulary for an outer axis whose grid does not contain its own posterior mode.

◆ Prediction

Expect tulpaObs to follow tulpa onto CRAN, since it is the consumer whose registrations the engine has spent this window unblocking, and expect the version line to move in larger, less frequent steps now that each one carries a submission.

Alternatives to gsDesign2 and tulpa

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 gsDesign2 or tulpa.

See all gsDesign2 alternatives → · See all tulpa alternatives →

Recent activity from gsDesign2 and tulpa

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

  1. 17h agotulpaFirst CRAN release: engine surface unchanged from 0.0.198
  2. 4d agotulpatulpa_re_aghq() exposes the mode/theta cross-Hessian
  3. 8d agotulpaDense batched joint path could silently drop a grid cell
  4. 8d agotulpaCalibration and goodness-of-fit entry points become S3 generics
  5. 9d agotulpaCUDA backend had two definitions; link order decided if it ran
  6. 9d agotulpaHyperparameter bounds now flag when they leave the node range
  7. 14d agogsDesign2Harm boundaries land in AHR and NPE group sequential designs
  8. 1mo agogsDesign2Conditional power, sequential p-values, and minimal risk weighting
  9. 6mo agogsDesign2gs_design_ahr() can output spending time
  10. 9mo agogsDesign2S3 class refactor and futility boundary vignette
  11. 11mo agogsDesign2h1_spending for WLR power, info_scale across fixed designs
  12. 1y agogsDesign2WLR design spending default corrected to information fraction

Frequently asked questions

What is the difference between gsDesign2 and tulpa?

They serve adjacent needs but don't currently overlap on shipped themes. tulpa is currently shipping more aggressively (velocity 7.5 vs 3.8), with 2 editorial sparks in the last 30 days against 1. See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.

Is gsDesign2 better than tulpa?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. tulpa is currently shipping more aggressively (velocity 7.5 vs 3.8), with 2 editorial sparks in the last 30 days against 1. For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.

What are the best alternatives to gsDesign2?

Top gsDesign2 alternatives in Analytics are ranked by recent ship velocity. Browse the "gsDesign2 alternatives" section above for the current picks, or visit /alternatives/gsdesign2 for the full list with editorial commentary on each.

What are the best alternatives to tulpa?

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