ggpointless
ggpointless keeps adding the ggplot2 layers nobody else bothered to write.
A side-by-side editorial comparison of prova and smam — release velocity, themes, recent moves, and the top alternatives to consider.
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.
Animal-movement models in R, where new stochastic processes arrive years apart.
smam fits statistical models of animal movement, covering moving-resting processes with and without measurement error, moving-resting-handling, and moving-moving processes, with simulation, point estimation and variance estimation for each. The last three releases are pure upkeep: guarding Rf_error calls after an Rcpp update, a maintainer email change, and a compiler warning fix. The substantive work in this window is 0.7.0, which added estimate and vcov generics across all fit functions, and 0.6.0, which added the moving-moving process.
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.
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.
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.
smam fits statistical models of animal movement, covering moving-resting processes with and without measurement error, moving-resting-handling, and moving-moving processes, with simulation, point estimation and variance estimation for each. The last three releases are pure upkeep: guarding Rf_error calls after an Rcpp update, a maintainer email change, and a compiler warning fix. The substantive work in this window is 0.7.0, which added estimate and vcov generics across all fit functions, and 0.6.0, which added the moving-moving process.
This package grows by adding process models, and it does so rarely. Between the moving-moving process in 2021 and now, the only interface-level change has been the 0.7.0 generics that gave every fit function a common way to retrieve estimates and their covariance, which is consolidation of an accumulated collection rather than expansion of it. The three releases since are entirely reactive to toolchain and CRAN pressure, and they arrive in step with the maintainer's other package coga, which received the same Rcpp guard within twenty minutes on the same day.
Expect further releases to be CRAN and Rcpp maintenance unless a new movement process is published, which is what has historically prompted a minor version here. The generics added in 0.7.0 give any future process model a ready-made interface to slot into.
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 prova or smam.
ggpointless keeps adding the ggplot2 layers nobody else bothered to write.
mpactr spent two spring releases normalizing case in metadata after users kept tripping on it.
surveytidy taught every dplyr verb to operate on a whole collection of surveys at once.
surveycore declared its API stable with every survey design type covered.
PEIMAN2 cut its annotation database loose from its release cycle without breaking CRAN.
prospectr spent its biggest release in years fixing spectra it had been quietly mangling.
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. 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.
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.
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.
Top smam alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "smam alternatives" section above for the current picks, or visit /alternatives/smam for the full list with editorial commentary on each.