tern.rbmi
Reference-based multiple imputation tables, shipping only what CRAN checks demand.
A side-by-side editorial comparison of enpls and xts — 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.
xts is finished software, and its releases now track R's C API more than user requests.
xts is the time-series class underpinning much of R's financial stack, and it behaves like infrastructure: the visible releases are bug fixes, plotting repairs and conformance work. A recurring thread is removing calls R no longer considers public — SET_TYPEOF in 0.14.0 and 0.14.1, then ATTRIB() and SET_ATTRIB() in 0.14.2. Feature additions are rare and small, the last cluster being open-ended time-of-day subsetting and na.fill performance in 0.13.0.
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.
xts is the time-series class underpinning much of R's financial stack, and it behaves like infrastructure: the visible releases are bug fixes, plotting repairs and conformance work. A recurring thread is removing calls R no longer considers public — SET_TYPEOF in 0.14.0 and 0.14.1, then ATTRIB() and SET_ATTRIB() in 0.14.2. Feature additions are rare and small, the last cluster being open-ended time-of-day subsetting and na.fill performance in 0.13.0.
Two forces drive releases. R core keeps narrowing its public C API, and xts keeps rewriting internals to stay inside it; separately, ggplot-era changes elsewhere in the ecosystem surface plotting bugs that get fixed one report at a time. Nearly every entry credits an outside reporter, which is what maintenance of a dependency this widely used looks like.
Further C API conformance work is the safest expectation, since two consecutive releases have each removed a different non-API entry point and R has continued tightening that boundary.
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 xts.
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 xts 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 xts 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 xts alternatives in Analytics are ranked by recent ship velocity. Browse the "xts alternatives" section above for the current picks, or visit /alternatives/xts-r for the full list with editorial commentary on each.