driveR
A cancer driver prioritization package that ships rarely and mostly to stay installable
Comparison · Infra & APIs
cvms vs missSBM
A side-by-side editorial comparison of cvms and missSBM — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-package
cvms vs missSBM: at a glance
What is cvms?
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.
What is missSBM?
missSBM returns after four dormant years with a stricter API and a new refinement step.
The package fits stochastic block models to networks with missing data, covering both missing-at-random and informative sampling designs. After a run of releases from 2019 to 2022, the feed goes quiet until this year's 1.1.0, which breaks the control interface, exposes the block split and merge operations as testable instance methods, and adds a node-swap refinement pass that runs after variational convergence.
cvms vs missSBM: editorial side-by-side
cvms
0.0INFRA · APIS
A cross-validation package whose real development has moved to its plotting function
◆ Current state
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.
◆ Where it's heading
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.
◆ Prediction
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.
missSBM
2.5INFRA · APIS
missSBM returns after four dormant years with a stricter API and a new refinement step.
◆ Current state
The package fits stochastic block models to networks with missing data, covering both missing-at-random and informative sampling designs. After a run of releases from 2019 to 2022, the feed goes quiet until this year's 1.1.0, which breaks the control interface, exposes the block split and merge operations as testable instance methods, and adds a node-swap refinement pass that runs after variational convergence.
◆ Where it's heading
The new release is maintenance-driven in the best sense: it targets the parts of the codebase that were hard to test or easy to misuse. Replacing free-form control lists with a function of named, defaulted arguments turns silent typos into errors, and pulling the exploration logic out of the collection class makes the search algorithm independently testable without changing it. The polish step addresses a known weakness, reaching individually misclassified nodes that split and merge moves cannot fix.
◆ Prediction
Given the gap before this release, the near-term question is whether the cadence resumes at all; the refactoring it contains would support further algorithmic work if it does.
Alternatives to cvms and missSBM
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 missSBM.
metR
A meteorology ggplot2 extension where the netCDF reader became the main event
IsoriX
An isotope geolocation package still recovering from the r-spatial retirement
fdacluster
Functional data clustering grew from one algorithm into a comparable suite
profoc
A forecast combination package that spun its profiler out into its own project
adjustedCurves
A survival curve package spending release after release correcting its own estimates
See all cvms alternatives → · See all missSBM alternatives →
Recent activity from cvms and missSBM
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 26d agomissSBMReplaces raw control lists with missSBM_param(), adds polish()
- 2mo agocvmsCoefficient extraction restored for multinom and mixed models
- 9mo agocvmsBreaking fix for mismatched folds with non-sequential fold IDs
- 11mo agocvmsTest compatibility with pROC 1.19 and a deprecation warning fix
- 1y agocvmsConfusion matrix fonts and colors can now be computed from the values
- 1y agocvmsTile intensity by row or column percentages
- 1y agocvmsMultinom coefficient extraction fix after a parameters update
- 3y agomissSBMAdapts to Matrix 1.4-2 and fixes HTML5 documentation
- 4y agomissSBMFixes linking against nloptR 2.0.0
- 5y agomissSBMRelaxes CRAN test tolerances to avoid random failures
- 5y agomissSBMRewrites optimisation in C++ armadillo with sparse matrices
- 5y agomissSBMRenames core functions and interfaces with the sbm package
Frequently asked questions
What is the difference between cvms and missSBM?
Both compete on the same themes — r-package — within Infra & APIs. missSBM 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 cvms better than missSBM?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. missSBM 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.
What are the best alternatives to cvms?
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.
What are the best alternatives to missSBM?
Top missSBM alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "missSBM alternatives" section above for the current picks, or visit /alternatives/misssbm for the full list with editorial commentary on each.