rollupTree
The recursive-computation engine under massProps grows the accessors its consumer needed
A side-by-side editorial comparison of gofedf and smam — release velocity, themes, recent moves, and the top alternatives to consider.
A two-test goodness-of-fit package opens itself up to any weight function
gofedf runs goodness-of-fit tests built on the empirical distribution function. Its three releases trace a short, clean arc: existence in 2023, then p-values computed from an analytical solution of the integral equation in 2024, then in 2026 a user-supplied weight function that replaces the fixed menu. Cramer-von Mises and Anderson-Darling are now two points in a family rather than the two options.
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.
gofedf runs goodness-of-fit tests built on the empirical distribution function. Its three releases trace a short, clean arc: existence in 2023, then p-values computed from an analytical solution of the integral equation in 2024, then in 2026 a user-supplied weight function that replaces the fixed menu. Cramer-von Mises and Anderson-Darling are now two points in a family rather than the two options.
The package is generalising rather than accumulating. Each release removed a hard-coded decision: first how eigenvalues are computed, offering both the analytical route and a matrix approximation; then which weight function defines the statistic at all. The maintainer's own framing in 1.1.0 is a contrast against what earlier versions would not let you do, which is the shape of a package aiming to become a framework.
An arbitrary weight function is the extensibility point that matters for EDF tests; what it lacks is calibration guidance, since Type I error behaviour was the argued benefit of the analytical eigenvalue route. Documented recommendations or diagnostics for user-chosen weights are the natural follow-up, though the entries do not announce one.
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 gofedf or smam.
The recursive-computation engine under massProps grows the accessors its consumer needed
A mass-properties rollup spends a year on documentation and follows its sibling's API
Six months of releases and not one of them touched the scoring models
A cognitive-science sampling package ships once, then goes quiet for eighteen months
A Bayesian volatility sampler in its maintenance decade, paying for its own speed
A black-box interpreter reaches CRAN, then learns multi-class and survival responses
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. gofedf and smam are shipping at a similar cadence (velocity 0.0 vs 0.0, both within Sparkpulse's "active" band). 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. gofedf and smam are shipping at a similar cadence (velocity 0.0 vs 0.0, both within Sparkpulse's "active" band). For your specific use case, the alternatives sections above list other Infra & APIs products to evaluate alongside.
Top gofedf alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "gofedf alternatives" section above for the current picks, or visit /alternatives/gofedf 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.