HydroPortailStats
France's national flood statistics, ported out of Fortran and into R.
A side-by-side editorial comparison of adjustedCurves and gkwdist — release velocity, themes, recent moves, and the top alternatives to consider.
A survival curve package spending release after release correcting its own estimates
adjustedCurves computes confounder-adjusted survival and cumulative incidence curves across a range of estimators - IPTW, AIPTW, Aalen-Johansen, direct standardisation - with support for multiple imputation and bootstrapping. The recent releases are dominated by corrections to numbers the package already reported. Version 0.11.4 fixed cumulative incidence estimates under method="aalen_johansen" that were being read one time step early, which the maintainer notes could differ substantially when events are few, and added risk and event counts to the ggsurvplot conversion including correctly pooled values under multiple imputation.
gkwdist keeps finding that its distributions were returning the wrong numbers.
The package implements the Generalized Kumaraswamy distribution family and its sub-families. The current release fixes six numerical defects, the most serious being that dgkw() returned zero for every input because internal helpers collided with same-named functions in R's public Rmath.h header. Log-likelihoods for three sub-families were also wrong for data near zero due to clamping instead of working in log space.
adjustedCurves computes confounder-adjusted survival and cumulative incidence curves across a range of estimators - IPTW, AIPTW, Aalen-Johansen, direct standardisation - with support for multiple imputation and bootstrapping. The recent releases are dominated by corrections to numbers the package already reported. Version 0.11.4 fixed cumulative incidence estimates under method="aalen_johansen" that were being read one time step early, which the maintainer notes could differ substantially when events are few, and added risk and event counts to the ggsurvplot conversion including correctly pooled values under multiple imputation.
Multiple imputation is the recurring fault line. The standard error pooling formula was implemented incorrectly until 0.11.2, then fixed again in 0.11.3 for the bootstrapping-plus-imputation combination, and 0.11.4 added the pooled risk table values that had previously been omitted entirely. A separate thread quietly removed capability: tmle and ostmle methods went in 0.10.0, and tmle support was pulled again in 0.11.1 after the concrete package left CRAN. Feature work does happen - risk tables, contrast arguments, the extend_to_last control on IPTW curves - but it is outweighed by correction.
Expect continued estimator-level corrections rather than new methods, and a possible return of tmle support if its upstream dependency returns to CRAN, since the removal was described as temporary.
The package implements the Generalized Kumaraswamy distribution family and its sub-families. The current release fixes six numerical defects, the most serious being that dgkw() returned zero for every input because internal helpers collided with same-named functions in R's public Rmath.h header. Log-likelihoods for three sub-families were also wrong for data near zero due to clamping instead of working in log space.
Every release in this window is correctness work with an unchanged public API — critical MLE fixes in 1.1.3, a CRAN timing-test patch in 1.1.4, numerical corrections in 1.1.5. The recurring theme is that analytically correct formulas were being defeated by implementation details: name collisions, sign errors returning negative infinity where positive was required, and clamping thresholds that destroyed precision in the tails. Test infrastructure added in 1.1.2 validates analytical derivatives against numerical differentiation, which is how several of these were caught.
Expect further validation-driven fixes rather than new distributions, since the derivative-checking suite added earlier is still surfacing defects in existing routines.
Other Infra & APIs 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 adjustedCurves or gkwdist.
France's national flood statistics, ported out of Fortran and into R.
Sign, zero and narrative restrictions brought into the bsvars ecosystem.
Fast design-based estimators for experiments, coasting on CRAN patches.
The grammar of uncertainty visualization, now drawing the uncertainty in its own estimates.
IP address vectors for R that hit 1.0 and then went quiet.
A column-key toolkit for stitching decades of ecological field data into one table.
See all adjustedCurves alternatives → · See all gkwdist alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-package — within Infra & APIs. gkwdist 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.
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. gkwdist 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 Infra & APIs products to evaluate alongside.
Top adjustedCurves alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "adjustedCurves alternatives" section above for the current picks, or visit /alternatives/adjustedcurves for the full list with editorial commentary on each.
Top gkwdist alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "gkwdist alternatives" section above for the current picks, or visit /alternatives/gkwdist for the full list with editorial commentary on each.