driveR
A cancer driver prioritization package that ships rarely and mostly to stay installable
A side-by-side editorial comparison of cvms and gkwdist — release velocity, themes, recent moves, and the top alternatives to consider.
A cross-validation package whose real development has moved to its plotting function
cvms runs repeated cross-validation over model formulas and reports comparable metrics. The 2.0.0 release was a breaking correctness fix: every function accepting fold_cols mismatched training and testing data when fold indices were non-sequential, did not start at 1, or were strings, because the iteration index was compared against the raw fold value rather than its factor level index. 2.0.1 restored coefficient extraction for nnet::multinom and mixed models by supplying an environment containing the training data, and followed lme4's move of findbars() into the reformulas package.
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.
cvms runs repeated cross-validation over model formulas and reports comparable metrics. The 2.0.0 release was a breaking correctness fix: every function accepting fold_cols mismatched training and testing data when fold indices were non-sequential, did not start at 1, or were strings, because the iteration index was compared against the raw fold value rather than its factor level index. 2.0.1 restored coefficient extraction for nnet::multinom and mixed models by supplying an environment containing the training data, and followed lme4's move of findbars() into the reformulas package.
Two threads run in parallel and only one is about cross-validation. The plotting function plot_confusion_matrix() has absorbed most feature work since 1.5.0 - custom gradient palettes, intensity limits, per-tile settings, dynamic font colors keyed to value thresholds, and arguments that accept functions rather than constants - to the point where a companion web application exists for using it without code. The cross-validation core, by contrast, sees maintenance: upstream compatibility fixes for pROC, ggnewscale and ggplot2, and the fold-matching correction that finally forced a major version.
Expect continued option growth in the confusion matrix plotting surface, since that is where nearly every release since 1.5.0 has spent its changes, with core cross-validation changes arriving only as upstream packages force them.
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 cvms or gkwdist.
A cancer driver prioritization package that ships rarely and mostly to stay installable
A meteorology ggplot2 extension where the netCDF reader became the main event
An isotope geolocation package still recovering from the r-spatial retirement
Functional data clustering grew from one algorithm into a comparable suite
A forecast combination package that spun its profiler out into its own project
A survival curve package spending release after release correcting its own estimates
See all cvms 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 cvms alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "cvms alternatives" section above for the current picks, or visit /alternatives/cvms 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.