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ggsurvfit vs tulpa

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

ggsurvfit vs tulpa: at a glance

Featureggsurvfittulpa
SectorAnalyticsAnalytics
Velocity score2.57.5
Sparks · 30d02
Top themessurvival-analysis, ggplot2, competing-risks, clinical-plotsbayesian-inference, cran-release, r-packages, spatial-modeling
Last editorial update5d ago8h ago
WebsiteVisit →Visit →

What is ggsurvfit?

ggsurvfit is in correctness-and-compatibility mode, not feature mode.

The package draws survival and cumulative-incidence curves on a ggplot2 grammar, with risk tables, p-values and quantile annotations. Recent releases are entirely fixes and upstream tracking: ggplot2 v4.0.0 compatibility in 2025, and a 2026 patch correcting a Gray-test p-value that could be reported for the wrong competing event.

Read the full ggsurvfit 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 →

ggsurvfit vs tulpa: editorial side-by-side

G
ggsurvfit
ANALYTICS
2.5

ggsurvfit is in correctness-and-compatibility mode, not feature mode.

◆ Current state

The package draws survival and cumulative-incidence curves on a ggplot2 grammar, with risk tables, p-values and quantile annotations. Recent releases are entirely fixes and upstream tracking: ggplot2 v4.0.0 compatibility in 2025, and a 2026 patch correcting a Gray-test p-value that could be reported for the wrong competing event.

◆ Where it's heading

The feature surface settled around 1.0.0, when risk-table alignment was exported and colour and linetype defaults became configurable. Since then the work is keeping pace with survival, ggplot2 and tidycmprsk changes, and closing cases where the plotted curve and the annotation disagreed — the p-value matched by position rather than name, confidence limits swapped for multi-state models, quantiles read off a plateau.

◆ Prediction

Expect the next release to track upstream survival or ggplot2 changes rather than add plotting features; the CDISC censoring convention adopted in Surv_CNSR() suggests further alignment with clinical data standards is the likelier direction.

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 ggsurvfit 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 ggsurvfit or tulpa.

See all ggsurvfit alternatives → · See all tulpa alternatives →

Recent activity from ggsurvfit 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. 26d agoggsurvfitGray-test p-values matched to the plotted outcome by name
  8. 10mo agoggsurvfitggplot2 v4.0.0 compatibility and multi-state CI label fix
  9. 2y agoggsurvfitNegative follow-up times and a cloglog transformation
  10. 2y agoggsurvfitAesthetic defaults become switchable and alignment is exported
  11. 2y agoggsurvfitConfidence limits corrected for monotonicity-reversing transforms
  12. 3y agoggsurvfitGlue syntax in risk tables and coxph model support

Frequently asked questions

What is the difference between ggsurvfit and tulpa?

They serve adjacent needs but don't currently overlap on shipped themes. tulpa is currently shipping more aggressively (velocity 7.5 vs 2.5), with 2 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 ggsurvfit 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 2.5), with 2 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 ggsurvfit?

Top ggsurvfit alternatives in Analytics are ranked by recent ship velocity. Browse the "ggsurvfit alternatives" section above for the current picks, or visit /alternatives/ggsurvfit 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.