PINstimation
A market-microstructure toolkit that keeps adding estimators as the papers land.
A side-by-side editorial comparison of ipeaplot and mice — release velocity, themes, recent moves, and the top alternatives to consider.
An institutional chart theme whose recent releases are all vignette repair.
ipeaplot supplies Ipea's house style to ggplot2 — theme_ipea(), matching colour and fill scales, and export helpers that write the formats the institute's publications need. The feature line has been quiet since October, when save_ipeaplot() consolidated the format-specific savers. Both July releases exist to get the package building again, not to change it.
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.
ipeaplot supplies Ipea's house style to ggplot2 — theme_ipea(), matching colour and fill scales, and export helpers that write the formats the institute's publications need. The feature line has been quiet since October, when save_ipeaplot() consolidated the format-specific savers. Both July releases exist to get the package building again, not to change it.
The package has been converging on a smaller, more uniform surface: separate save_eps() and save_pdf() helpers gave way to one save_ipeaplot() covering vector and raster formats with sensible defaults, and the Frutiger font dependency was dropped for a default sans-serif. What consumes releases now is downstream breakage — two consecutive patches in ten days, the second traced to geobr, both in vignettes rather than package code.
The palette line has grown one colour set at a time and is the most likely place for the next addition, but nothing in these entries commits to it. On current evidence the near term is more compatibility patching against the geobr and ggplot2 packages the vignettes depend on.
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.
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 ipeaplot or mice.
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.
A Bayesian model-averaging package spending its 2.0 on memory, not methods.
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.
See all ipeaplot alternatives → · See all mice alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. ipeaplot and mice 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. ipeaplot and mice 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 ipeaplot alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "ipeaplot alternatives" section above for the current picks, or visit /alternatives/ipeaplot for the full list with editorial commentary on each.
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.