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mice vs smam

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

mice vs smam: at a glance

Featuremicesmam
SectorInfra & APIsInfra & APIs
Velocity score0.00.0
Sparks · 30d00
Top themesmissing-data, multiple-imputation, statistics, r-packageanimal-movement, stochastic-processes, state-space-models, rcpp
Last editorial update58m ago5h ago
WebsiteVisit →Visit →

What is mice?

mice can finally predict, not just estimate, from multiply imputed data.

mice is the reference implementation of multiple imputation by chained equations, and the default answer to missing data in R. The releases here follow a consistent shape: one or two substantive additions per version, most contributed by outside authors, plus fixes to methods that have been in the package for years. The current 3.19.0 adds predict_mi(), which pools predictions across imputations under Rubin's rules and can return prediction intervals.

Read the full mice trajectory →

What is smam?

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.

Read the full smam trajectory →

mice vs smam: editorial side-by-side

M
mice
INFRA · APIS
0.0

mice can finally predict, not just estimate, from multiply imputed data.

◆ Current state

mice is the reference implementation of multiple imputation by chained equations, and the default answer to missing data in R. The releases here follow a consistent shape: one or two substantive additions per version, most contributed by outside authors, plus fixes to methods that have been in the package for years. The current 3.19.0 adds predict_mi(), which pools predictions across imputations under Rubin's rules and can return prediction intervals.

◆ Where it's heading

Two things are happening. The imputation method catalogue keeps widening — lasso variants, multivariate PMM, categorical PMM via canonical correlation — while the pooling side is being extended past its original purpose, first to synthetic data, now to predictions on held-out sets. That second thread points at predictive modelling workflows rather than the inferential ones mice was built for. Meanwhile the maintainers keep finding consequential old bugs: the augment() ordered-factor defect in 3.18.0 had been silently degrading ordinal imputations for years.

◆ Prediction

predict_mi() is framed around evaluating predictive performance on test sets, and the ignore argument added in 3.12.0 already exists to hold out rows from the imputation model. Expect the next work to join those up into a fuller train/test story for imputed data, since the pieces are now in place but not yet connected.

S
smam
INFRA · APIS
0.0

Animal-movement models in R, where new stochastic processes arrive years apart.

◆ Current state

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.

◆ Where it's heading

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.

◆ Prediction

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.

Alternatives to mice and smam

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 mice or smam.

See all mice alternatives → · See all smam alternatives →

Recent activity from mice and smam

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

  1. 5mo agosmamRcpp attributes regenerated to guard Rf_error calls
  2. 8mo agomicemice 3.19.0
  3. 1y agomicemice 3.18.0
  4. 1y agomicemice 3.17.0
  5. 2y agosmamMaintainer email updated
  6. 2y agosmamCompiler format-security warning resolved
  7. 3y agosmamestimate and vcov generics unify all fit functions
  8. 3y agomicemice 3.16.0
  9. 3y agomicemice 3.15.0
  10. 4y agomicemice 3.14.0
  11. 5y agosmamMoving-moving process added with simulation and estimation
  12. 5y agosmamVariance estimators adjusted; example dataset added

Frequently asked questions

What is the difference between mice and smam?

They serve adjacent needs but don't currently overlap on shipped themes. mice 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.

Is mice better than smam?

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

What are the best alternatives to mice?

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

What are the best alternatives to smam?

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.