tern.rbmi
Reference-based multiple imputation tables, shipping only what CRAN checks demand.
A side-by-side editorial comparison of enpls and ggsci — release velocity, themes, recent moves, and the top alternatives to consider.
enpls has not changed its statistics since 2016 — only its website, twice.
enpls implements ensemble partial least squares regression, with variants for feature selection, outlier detection and model applicability. Across the six most recent releases there is not one change to the modeling code. They cover a documentation website, a website URL change, a font stack, code indentation, a CI service, and most recently a GitHub Actions migration with an R CMD check note fix.
ggsci quietly became a palette mirror, then taught itself to generate colors on demand
ggsci ships ready-made ggplot2 color scales, originally journal and sci-fi palettes and now overwhelmingly terminal themes — the iTerm collection has grown past 400 entries and picks up 30 to 70 more with each sync. The one structural change in the recent run is gephi_palettes(), which generates distinct categorical colors for an arbitrary number of levels rather than serving a fixed list. Release cadence is steady, roughly every six to eight weeks.
enpls implements ensemble partial least squares regression, with variants for feature selection, outlier detection and model applicability. Across the six most recent releases there is not one change to the modeling code. They cover a documentation website, a website URL change, a font stack, code indentation, a CI service, and most recently a GitHub Actions migration with an R CMD check note fix.
The statistical work finished around version 5.6, which added cross-validation fold control and fixed component selection when the maximum was left unspecified. Everything since has kept the package installable and its docs online. The 2025 release arriving the same day as sibling package grex, with the same two fixes, confirms the pattern: these are maintainer sweeps across a portfolio, not attention to enpls specifically.
The next release will almost certainly be another CRAN or tooling fix. Six consecutive infrastructure-only releases across nine years give no basis for expecting new methods.
ggsci ships ready-made ggplot2 color scales, originally journal and sci-fi palettes and now overwhelmingly terminal themes — the iTerm collection has grown past 400 entries and picks up 30 to 70 more with each sync. The one structural change in the recent run is gephi_palettes(), which generates distinct categorical colors for an arbitrary number of levels rather than serving a fixed list. Release cadence is steady, roughly every six to eight weeks.
Two threads run in parallel. The larger one is curation: ggsci has effectively become a distribution channel for upstream color work, adding design-system palettes (Primer, Atlassian, Bootstrap, Tailwind) and re-syncing iTerm as that project changes, including correcting existing color values when upstream moves. The smaller and more interesting one is generation — the Gephi engine sidesteps the ceiling every fixed palette has, which is what happens when a plot needs more categories than any curated set provides.
Given how much of the release notes each cycle is a mechanical upstream sync, the plausible next step is automating those syncs rather than adding another vendor palette by hand; the Gephi generator is the more likely place any genuinely new capability appears.
Other Analytics 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 enpls or ggsci.
Reference-based multiple imputation tables, shipping only what CRAN checks demand.
An MMRM tabulation package that has published nothing since its 2024 CRAN releases.
A single-purpose ggplot2 inset tool, refining the same three arguments.
An R symbolic-maths binding whose changelog is really the C++ core's release notes.
gtfstools stopped guarding its own object model and started accepting everyone else's.
The glue package that makes R carry units and uncertainty through the same calculation.
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. ggsci is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. 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. ggsci is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.
Top enpls alternatives in Analytics are ranked by recent ship velocity. Browse the "enpls alternatives" section above for the current picks, or visit /alternatives/enpls for the full list with editorial commentary on each.
Top ggsci alternatives in Analytics are ranked by recent ship velocity. Browse the "ggsci alternatives" section above for the current picks, or visit /alternatives/ggsci for the full list with editorial commentary on each.