ggpointless
ggpointless keeps adding the ggplot2 layers nobody else bothered to write.
Comparison · Infra & APIs
plssem vs prova
A side-by-side editorial comparison of plssem and prova — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-packages
plssem vs prova: at a glance
| Feature | plssem | prova |
|---|---|---|
| Sector | Infra & APIs | Infra & APIs |
| Velocity score | 0.0 | 6.3 |
| Sparks · 30d | 0 | 1 |
| Top themes | structural-equation-modeling, partial-least-squares, multilevel-models, standard-errors | r-packages, bayesian-inference, decision-analysis, api-consolidation |
| Last editorial update | 44m ago | 1h ago |
| Website | Visit → | Visit → |
What is plssem?
plssem took PLS-SEM into multilevel data, then spent two releases making the estimates trustworthy.
plssem is a young R implementation of partial least squares structural equation modelling, three CRAN releases old and shipping monthly. Its distinguishing work is the MC-PLS family — consistent PLS estimators the maintainer extended to mixed-effects designs in June — and the releases since have been about getting standard errors, admissibility and fit measures onto the same footing as the point estimates.
What is prova?
prova adds expected-utility calculation on top of its Bayesian inference core.
prova does Bayesian nonparametric inference in R — probabilities through Pr() and qPr(), mutual information, quantile plots. Five releases in about two weeks renamed its central argument, collapsed two plotting functions into one, and then in v2.3.0 introduced exputility() for expected utilities and their revisability, with plot() and print() methods attached from the start.
plssem vs prova: editorial side-by-side
plssem
0.0INFRA · APIS
plssem took PLS-SEM into multilevel data, then spent two releases making the estimates trustworthy.
◆ Current state
plssem is a young R implementation of partial least squares structural equation modelling, three CRAN releases old and shipping monthly. Its distinguishing work is the MC-PLS family — consistent PLS estimators the maintainer extended to mixed-effects designs in June — and the releases since have been about getting standard errors, admissibility and fit measures onto the same footing as the point estimates.
◆ Where it's heading
The pattern is capability first, inference second. Multilevel MC-PLSc and MC-OrdPLSc arrived in 0.1.2 together with Monte-Carlo delta-method standard errors and a Polyak-Juditsky extrapolation step; 0.1.3 then extended delta-method errors to redundant parameters and thresholds, optimized their computation, added a loglikelihood-based fit measure and generated dynamic bounds to keep MC-PLS solutions admissible. Admissibility recurs throughout — penalized inadmissible solutions in 0.1.1, variance lower bounds and negative residual variance handling in 0.1.3, and an option to drop inadmissible bootstraps rather than silently include them. The release notes are pull-request lists, so the reasoning behind each change stays in the repository.
◆ Prediction
The MIMIC mode and GLS estimator both landed in the most recent release without the standard-error and fit-measure work that followed earlier additions, so extending inference to cover them is the natural next step. Bootstrap defaults moving to 500 replications suggests runtime is a live constraint and further optimization is likely.
prova
6.3INFRA · APIS
prova adds expected-utility calculation on top of its Bayesian inference core.
◆ Current state
prova does Bayesian nonparametric inference in R — probabilities through Pr() and qPr(), mutual information, quantile plots. Five releases in about two weeks renamed its central argument, collapsed two plotting functions into one, and then in v2.3.0 introduced exputility() for expected utilities and their revisability, with plot() and print() methods attached from the start.
◆ Where it's heading
Two arcs run in parallel. One compresses the API: learnt= became K=, flexiplot() and plotquantiles() merged into pplot(), and omitting arguments such as Y=, X= and K= got simpler. The other extends reach — mutualinfoF() for finite-domain variates, quantile accuracy reported alongside mutual information, and now a decision-theoretic layer sitting on the inference the package already did.
◆ Prediction
exputility() shipping with print() and plot() methods matches how the probability and mutual-information classes were treated, so utilities are likely to get the same class-based handling as they mature. The notes do not say whether decision analysis extends beyond expected utility.
Alternatives to plssem and prova
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 plssem or prova.
mpactr
mpactr spent two spring releases normalizing case in metadata after users kept tripping on it.
surveytidy
surveytidy taught every dplyr verb to operate on a whole collection of surveys at once.
surveycore
surveycore declared its API stable with every survey design type covered.
PEIMAN2
PEIMAN2 cut its annotation database loose from its release cycle without breaking CRAN.
prospectr
prospectr spent its biggest release in years fixing spectra it had been quietly mangling.
See all plssem alternatives → · See all prova alternatives →
Recent activity from plssem and prova
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 13d agoprovaexputility() brings decision analysis into prova ⚡
- 20d agoprovaCumulative 2.x notes, plus hist() and mutual-information changes
- 23d agoprovalearnt= becomes K=; pplot() replaces two plot functions
- 27d agoprovaFix for pre-existing parallel clusters
- 28d agoprovaextraDistr dropped; mutual-information objects get a class
- 1mo agoplssemMIMIC mode, a GLS structural estimator and delta-method thresholds
- 2mo agoplssemMC-PLSc and MC-OrdPLSc extend to multilevel and mixed-effects models ⚡
- 3mo agoplssemParallel bootstrapping, kNN and mean imputation, higher-order constructs
Frequently asked questions
What is the difference between plssem and prova?
Both compete on the same themes — r-packages — within Infra & APIs. prova is currently shipping more aggressively (velocity 6.3 vs 0.0), with 1 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 plssem better than prova?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. prova is currently shipping more aggressively (velocity 6.3 vs 0.0), with 1 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 plssem?
Top plssem alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "plssem alternatives" section above for the current picks, or visit /alternatives/plssem for the full list with editorial commentary on each.
What are the best alternatives to prova?
Top prova alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "prova alternatives" section above for the current picks, or visit /alternatives/prova for the full list with editorial commentary on each.