← Back to home
Comparison · Analytics

dfms vs marquee

A side-by-side editorial comparison of dfms and marquee — release velocity, themes, recent moves, and the top alternatives to consider.

dfms vs marquee: at a glance

Featuredfmsmarquee
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesnowcasting, state-space-models, econometrics, ropenscir-lib, typography, markdown, ggplot2
Last editorial update1h ago2h ago
WebsiteVisit →Visit →

What is dfms?

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.

Read the full dfms trajectory →

What is marquee?

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.

Read the full marquee trajectory →

dfms vs marquee: editorial side-by-side

D
dfms
ANALYTICS
0.0

Peer-reviewed, feature-complete, and now able to hand its models to other forecasting engines.

◆ Current state

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.

◆ Where it's heading

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.

◆ Prediction

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.

M
marquee
ANALYTICS
0.0

marquee is filling in the typographic details — outlines, border types, real font metrics for underlines.

◆ Current state

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.

◆ Where it's heading

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.

◆ Prediction

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.

Alternatives to dfms and marquee

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.

See all dfms alternatives → · See all marquee alternatives →

Recent activity from dfms and marquee

Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.

  1. 1mo agodfmsconvert() exports models to dlm and KFAS state-space objects
  2. 6mo agodfms1.0: rOpenSci review passed, news decomposition added
  3. 6mo agodfmsMixed-frequency estimation gains AR(1) idiosyncratic errors
  4. 9mo agodfmsC++ compatibility with RcppArmadillo 15.0.2
  5. 11mo agomarqueeBug fixes for relative sizes, outlines and guide width
  6. 11mo agomarqueeBorder and outline line types; underlines follow font metrics
  7. 11mo agomarqueeRotated text width fixed; factor input supported
  8. 0y agomarqueeText outlines, size shortcuts and images from URLs
  9. 1y agodfmsFixes estimation with a single quarterly variable
  10. 1y agodfmsAdds mixed-frequency estimation via quarterly.vars
  11. 1y agomarquee1.0 settles margin collapsing and inline decoration spacing

Frequently asked questions

What is the difference between dfms and marquee?

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.

Is dfms better than marquee?

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.

What are the best alternatives to dfms?

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.

What are the best alternatives to marquee?

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.