datefixR
The messy-date parser rewrote its core in Rust and came out 300x faster.
A side-by-side editorial comparison of dfms and marquee — release velocity, themes, recent moves, and the top alternatives to consider.
Peer-reviewed, feature-complete, and now able to hand its models to other forecasting engines.
dfms estimates dynamic factor models in R, the workhorse for nowcasting economic activity from ragged, mixed-frequency data. The package worked through the Banbura and Modugno (2014) specification in stages — quarterly variables in 0.3.0, AR(1) idiosyncratic errors combined with mixed frequency in 0.4.0 — then declared 1.0.0 feature-complete on completing rOpenSci peer review, adding news decomposition to attribute forecast revisions to specific data releases. Version 1.0.1 adds convert(), which exports fitted models to dlm or KFAS state-space objects.
marquee is filling in the typographic details — outlines, border types, real font metrics for underlines.
marquee renders markdown text onto R graphics devices, and backs element_marquee() and geom_marquee() in ggplot2. Development ran in a tight burst through August and September 2025: 1.1.0 added text outlines, a size shortcut and remote PNG/JPEG support, 1.2.0 added border and outline line types and moved underline placement onto font metrics, and 1.2.1 cleaned up the bugs those introduced.
dfms estimates dynamic factor models in R, the workhorse for nowcasting economic activity from ragged, mixed-frequency data. The package worked through the Banbura and Modugno (2014) specification in stages — quarterly variables in 0.3.0, AR(1) idiosyncratic errors combined with mixed frequency in 0.4.0 — then declared 1.0.0 feature-complete on completing rOpenSci peer review, adding news decomposition to attribute forecast revisions to specific data releases. Version 1.0.1 adds convert(), which exports fitted models to dlm or KFAS state-space objects.
The package has finished the implementation programme it set out in its 2023 vignette and is now working on the edges: interoperability with other state-space packages rather than more estimation methods of its own. The convert() function is the clearest signal — instead of implementing smoothing and prediction intervals natively, it hands the model to packages that already have them. The rOpenSci move also puts it on a review-backed, documented footing that research users can cite.
Expect continued interoperability and diagnostic work rather than new estimators, since the maintainer has explicitly scoped the package as complete. Bug fixes against RcppArmadillo releases will likely remain the other recurring driver.
marquee renders markdown text onto R graphics devices, and backs element_marquee() and geom_marquee() in ggplot2. Development ran in a tight burst through August and September 2025: 1.1.0 added text outlines, a size shortcut and remote PNG/JPEG support, 1.2.0 added border and outline line types and moved underline placement onto font metrics, and 1.2.1 cleaned up the bugs those introduced.
The package is converging on typographic fidelity rather than new capability. Early work settled layout semantics — CSS margin collapsing, inline padding reserving space during shaping, devices without glyph support — and recent releases refine how decorations are drawn and measured. The naming cleanup in 1.2.0, border_size becoming border_width, reads as an API being tidied ahead of wider use rather than one still being explored.
Expect continued small releases sanding down rendering edge cases in ggplot2 contexts, since that is where the recent bug reports come from; nothing here signals a new feature area.
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 dfms or marquee.
The messy-date parser rewrote its core in Rust and came out 300x faster.
The legend engine mapsf spun out, now covering legend types the parent map package can draw.
R help pages translated on demand by whichever LLM you point it at.
Thematic mapping in base R that finally got a theming system, then spent two years polishing legends.
qualtRics moved its contact functions onto XM Directory days before the old endpoints died.
The tidyverts forecasting core rebuilt model combination on full residual covariance.
See all dfms alternatives → · See all marquee alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. dfms and marquee 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. dfms and marquee 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 dfms alternatives in Analytics are ranked by recent ship velocity. Browse the "dfms alternatives" section above for the current picks, or visit /alternatives/dfms for the full list with editorial commentary on each.
Top marquee alternatives in Analytics are ranked by recent ship velocity. Browse the "marquee alternatives" section above for the current picks, or visit /alternatives/marquee for the full list with editorial commentary on each.