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Comparison · Infra & APIs

cvms vs sps

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

Shared themes:r-package

cvms vs sps: at a glance

Featurecvmssps
SectorInfra & APIsInfra & APIs
Velocity score0.02.5
Sparks · 30d00
Top themescross-validation, r-package, model-evaluation, visualizationr-package, survey-sampling, sequential-poisson, performance
Last editorial update1h ago2h ago
WebsiteVisit →Visit →

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.

Read the full cvms trajectory →

What is sps?

sps keeps sanding down sequential Poisson sampling rather than adding to it.

The package implements sequential Poisson sampling for survey design, covering inclusion probabilities, proportional allocation, replicate weights, and take-all strata. Recent releases are small and tightly scoped: a divisor method helper, an iterator that draws a sample one unit at a time, automatic selection of the replicate-weight parameter, and repeated performance work on inclusion probability calculation.

Read the full sps trajectory →

cvms vs sps: editorial side-by-side

C
cvms
INFRA · APIS
0.0

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.

S
sps
INFRA · APIS
2.5

sps keeps sanding down sequential Poisson sampling rather than adding to it.

◆ Current state

The package implements sequential Poisson sampling for survey design, covering inclusion probabilities, proportional allocation, replicate weights, and take-all strata. Recent releases are small and tightly scoped: a divisor method helper, an iterator that draws a sample one unit at a time, automatic selection of the replicate-weight parameter, and repeated performance work on inclusion probability calculation.

◆ Where it's heading

Development is consolidation rather than expansion. Most releases either speed up an existing routine or remove a decision the user previously had to make by hand, such as picking the smallest parameter that keeps replicate weights non-negative. Documentation and tooling get comparable attention to the algorithms, with a dedicated vignette on inclusion probabilities and a recent switch of test and documentation infrastructure. The API surface has been essentially stable across the window.

◆ Prediction

Expect continued small ergonomic and performance releases against the existing function set rather than new sampling designs, which is the pattern every release in this window follows.

Alternatives to cvms and sps

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 sps.

See all cvms alternatives → · See all sps alternatives →

Recent activity from cvms and sps

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

  1. 1mo agospsDocumentation polish; switches to tinytest and litedown
  2. 2mo agocvmsCoefficient extraction restored for multinom and mixed models
  3. 9mo agospsFixes extra argument handling in sps_iterator()
  4. 9mo agocvmsBreaking fix for mismatched folds with non-sequential fold IDs
  5. 11mo agocvmsTest compatibility with pROC 1.19 and a deprecation warning fix
  6. 11mo agospsAdds divisor_method() and a one-unit-at-a-time sampling iterator
  7. 1y agospsAdds an inclusion-probability vignette and faster partial sorting
  8. 1y agocvmsConfusion matrix fonts and colors can now be computed from the values
  9. 1y agocvmsTile intensity by row or column percentages
  10. 1y agospsAutomatic tau selection for replicate weights
  11. 1y agocvmsMultinom coefficient extraction fix after a parameters update
  12. 2y agospsAdds becomes_ta() for take-all stratum sample sizes

Frequently asked questions

What is the difference between cvms and sps?

Both compete on the same themes — r-package — within Infra & APIs. sps 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 sps?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. sps 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 sps?

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