tern.rbmi
Reference-based multiple imputation tables, shipping only what CRAN checks demand.
A side-by-side editorial comparison of errors and timeplyr — release velocity, themes, recent moves, and the top alternatives to consider.
errors keeps making uncertainty print the way each scientific field expects.
errors attaches uncertainty to numeric vectors and propagates it automatically through arithmetic, as part of the r-quantities family alongside units. The propagation core is settled; recent releases concentrate on presentation and integration — PDG rounding rules in 0.4.2, decimal support in parenthesis notation in 0.4.3, and ggplot2 deprecation tracking in 0.4.1 and 0.4.4.
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.
errors attaches uncertainty to numeric vectors and propagates it automatically through arithmetic, as part of the r-quantities family alongside units. The propagation core is settled; recent releases concentrate on presentation and integration — PDG rounding rules in 0.4.2, decimal support in parenthesis notation in 0.4.3, and ggplot2 deprecation tracking in 0.4.1 and 0.4.4.
Two threads run through this history. One is formatting convergence: uncertainty has field-specific conventions, and the package has been absorbing them one contributed pull request at a time rather than imposing a single style. The other is keeping the errors class first-class everywhere R users work — vctrs methods for dplyr 1.0, a geom_errors() layer for ggplot2, missing-value and duplicate handling. Both are integration work, which is what a type-extension package mostly is.
Expect further formatting conventions to arrive as contributions, following PDG rounding and the decimals option, plus continued upkeep against ggplot2 aesthetic deprecations that have forced two of the last four releases.
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 errors 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 errors 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. errors 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. errors 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 errors alternatives in Analytics are ranked by recent ship velocity. Browse the "errors alternatives" section above for the current picks, or visit /alternatives/errors-r 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.