tern.rbmi
Reference-based multiple imputation tables, shipping only what CRAN checks demand.
A side-by-side editorial comparison of enpls and timeplyr — 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.
timeplyr cut everything that wasn't time, then rebuilt intervals as fixed-width vectors.
timeplyr is a time-aware companion to dplyr and data.table, built around a fixed-width time_interval vector class. The 1.0.0 rewrite removed most non-time functions and pushed the C++ layer out into the separate cheapr package, leaving a narrower surface than the 0.8.x line. Releases since have been small: one feature batch in 1.1.1 and a pair of bug fixes in 1.1.2.
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.
timeplyr is a time-aware companion to dplyr and data.table, built around a fixed-width time_interval vector class. The 1.0.0 rewrite removed most non-time functions and pushed the C++ layer out into the separate cheapr package, leaving a narrower surface than the 0.8.x line. Releases since have been small: one feature batch in 1.1.1 and a pair of bug fixes in 1.1.2.
The arc is consolidation, not expansion. Each release since 1.0.0 trims arguments, renames functions toward a single vocabulary (width, timespan, grid), or fixes an interaction with data.table's own rolling functions. The package increasingly acts as a thin time layer over cheapr and data.table rather than carrying its own implementation.
Expect continued small releases tracking cheapr and data.table changes rather than new function families; the entries show no in-progress feature work beyond the ggplot2-friendly breakpoint helpers introduced in 1.1.1.
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 timeplyr.
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.
See all enpls alternatives → · See all timeplyr alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. enpls and timeplyr 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 timeplyr 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 timeplyr alternatives in Analytics are ranked by recent ship velocity. Browse the "timeplyr alternatives" section above for the current picks, or visit /alternatives/timeplyr for the full list with editorial commentary on each.