mice
mice can finally predict, not just estimate, from multiply imputed data.
A side-by-side editorial comparison of BAS and smam — release velocity, themes, recent moves, and the top alternatives to consider.
A Bayesian model-averaging package spending its 2.0 on memory, not methods.
BAS performs Bayesian variable selection and model averaging for linear and generalized linear models, sampling from a model space too large to enumerate. The visible history splits cleanly: 2023-2024 added sampling machinery — an adaptive independent MCMC sampler with Horvitz-Thompson estimation, hereditary-constraint counting — while 2.0.0 in late 2025 reworked how sampler output is allocated in C. The 2.0.2 patch is a PROTECT fix for rchk warnings.
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.
BAS performs Bayesian variable selection and model averaging for linear and generalized linear models, sampling from a model space too large to enumerate. The visible history splits cleanly: 2023-2024 added sampling machinery — an adaptive independent MCMC sampler with Horvitz-Thompson estimation, hereditary-constraint counting — while 2.0.0 in late 2025 reworked how sampler output is allocated in C. The 2.0.2 patch is a PROTECT fix for rchk warnings.
Memory is the binding constraint and the releases say so directly. The hereditary-constraint counter, the GROW option, and the replacement of over-allocation with resizing all attack the same problem: n.models is a guess, and guessing high wastes memory on problems where few unique models are actually visited. The 2.0.0 work was additionally forced by R tightening its C API against non-API calls like SETLENGTH, a constraint every C-heavy CRAN package has been absorbing. Method development has been quiet since 1.7.x.
The 1.7.5 notes call the hereditary-constraint counting a first step and say future updates will cover other constraint types, including polynomials, which remain unhandled. That is the one concrete commitment in this history, though nothing since has returned to it.
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 BAS or smam.
mice can finally predict, not just estimate, from multiply imputed data.
A market-microstructure toolkit that keeps adding estimators as the papers land.
A vowel-analysis package trimming dependencies after an email address got it archived.
The R half of the EMU speech database system, fixing what was quietly broken.
tidyplots keeps rebuilding its own foundations rather than layering around them.
A GENCODE annotation toolkit spent its first year getting out of CRAN's way.
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. BAS 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. BAS 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 BAS alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "BAS alternatives" section above for the current picks, or visit /alternatives/bas 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.