tern.rbmi
Reference-based multiple imputation tables, shipping only what CRAN checks demand.
A side-by-side editorial comparison of enpls and tmap — 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.
Two years after a from-scratch rewrite, tmap is filling in the layers v4 promised.
tmap draws thematic maps in R across static and interactive modes. The 4.0 rewrite replaced the layer syntax with explicit visual variables, scales, legends and charts, and opened the package to extensions; the 4.x line since has been steady capability fill-in. The 4.4 release adds tm_circles with fixed unit-based radii, a blend argument on every layer, and hitboxes so small objects stay clickable in view mode.
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.
tmap draws thematic maps in R across static and interactive modes. The 4.0 rewrite replaced the layer syntax with explicit visual variables, scales, legends and charts, and opened the package to extensions; the 4.x line since has been steady capability fill-in. The 4.4 release adds tm_circles with fixed unit-based radii, a blend argument on every layer, and hitboxes so small objects stay clickable in view mode.
The extension mechanism introduced in 4.0 is where the interesting work is migrating: PMTiles support arrived through a separate experimental tmap.sources package, mode cycling became configurable via tmap_mode_pool() so packages like tmap.mapgl can register themselves, and shiny dispatch methods were added specifically to let other modes integrate. The core package is increasingly a rendering contract that satellite packages plug into.
Expect more rendering backends to land as sibling packages rather than in tmap itself, with the core continuing to absorb the dispatch and mode-management plumbing they need.
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 tmap.
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. enpls and tmap 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. enpls and tmap 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 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 tmap alternatives in Analytics are ranked by recent ship velocity. Browse the "tmap alternatives" section above for the current picks, or visit /alternatives/tmap-r for the full list with editorial commentary on each.