jSDM
Joint species distribution models in Gibbs-sampled C++, quiet since 2023.
A side-by-side editorial comparison of mice and standardlastprofile — release velocity, themes, recent moves, and the top alternatives to consider.
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.
A German electricity load-profile package added gas and doubled the market it serves.
standardlastprofile implements the BDEW standard load profiles that German utilities use to assign consumption to customers without interval metering. Until June it did electricity only. Version 2.0.0 added the gas side — the SigLinDe synthetic procedure across all 15 BDEW gas profile IDs — and gave electricity a new primary interface, slp_electricity(), with slp_generate() superseded but retained.
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.
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.
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.
standardlastprofile implements the BDEW standard load profiles that German utilities use to assign consumption to customers without interval metering. Until June it did electricity only. Version 2.0.0 added the gas side — the SigLinDe synthetic procedure across all 15 BDEW gas profile IDs — and gave electricity a new primary interface, slp_electricity(), with slp_generate() superseded but retained.
The package is converting from a dataset wrapper into a calculation library. Electricity profiles are tabulated values the package ships; gas profiles are computed from daily temperatures and a customer value through a coefficient-driven function, and the maintainer exposed the whole ladder — slp_gas() for the profile, slp_gas_kundenwert() to derive the customer value from a reference year, slp_gas_siglinde() for the raw h(theta) demand function so users can supply state-level coefficients, and coefficient and weekday-factor accessors underneath. The same instinct removed the built-in holiday table in favour of computing Easter directly, which lifted the date range cap from 2073 to open-ended. Deprecations are handled carefully throughout: renames keep working with lifecycle warnings, and the one hard break was already a warning since 1.1.0.
slp_gas_siglinde() was exported specifically so users could plug in region-specific coefficients such as Baden-Wurttemberg's, which points at state-level coefficient sets as the next thing to ship rather than leave to callers. The BDEW reference edition is now pinned to an Internet Archive permalink after the last one 404'd, so tracking edition changes is an ongoing maintenance cost.
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 standardlastprofile.
Joint species distribution models in Gibbs-sampled C++, quiet since 2023.
An ecosystem model starts tracking carbon isotopes and land-use change.
Ten years in, US mapping splits its data out and finally adds Puerto Rico.
Fitness-tracking analysis in slow maintenance, still absorbing upstream breakage.
State-panel tooling holding steady since its 2020 data and ergonomics release.
Five years of compiler and CRAN fixes on a capture-recapture package.
See all mice alternatives → · See all standardlastprofile alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. mice and standardlastprofile 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. mice and standardlastprofile 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 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.
Top standardlastprofile alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "standardlastprofile alternatives" section above for the current picks, or visit /alternatives/standardlastprofile for the full list with editorial commentary on each.