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dfms vs rlistings

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

dfms vs rlistings: at a glance

Featuredfmsrlistings
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesnowcasting, state-space-models, econometrics, ropensciclinical-trials, listings, pagination, r-package
Last editorial update4h ago57m 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 rlistings?

Clinical listings that keep inheriting their hardest problem — pagination — from the layer below.

rlistings renders clinical-trial subject listings and paginates them for regulatory output, sitting alongside rtables on the shared formatters engine. The releases in this window are dominated by pagination correctness: repeated key columns across pages, splitting by a variable, ordered-factor handling, column gaps, and font metrics. Development is a large rotating contributor set inside the insightsengineering organisation.

Read the full rlistings trajectory →

dfms vs rlistings: 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.

R
rlistings
ANALYTICS
0.0

Clinical listings that keep inheriting their hardest problem — pagination — from the layer below.

◆ Current state

rlistings renders clinical-trial subject listings and paginates them for regulatory output, sitting alongside rtables on the shared formatters engine. The releases in this window are dominated by pagination correctness: repeated key columns across pages, splitting by a variable, ordered-factor handling, column gaps, and font metrics. Development is a large rotating contributor set inside the insightsengineering organisation.

◆ Where it's heading

The package is progressively delegating pagination to formatters rather than implementing it — paginate_listing() was refactored to call formatters' paginate_to_mpfs() directly, and truetype font support arrived through a new formatters API. That reduces duplicated logic but ties the package's page-break behaviour to a dependency it shares with rtables. Feature work beyond pagination is thin: better error messages for unsupported column classes, a cheatsheet.

◆ Prediction

Expect pagination fidelity to remain the focus, with changes arriving as formatters exposes more of its layout machinery rather than as rlistings-native features.

Alternatives to dfms and rlistings

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 rlistings.

See all dfms alternatives → · See all rlistings alternatives →

Recent activity from dfms and rlistings

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. 1y agodfmsFixes estimation with a single quarterly variable
  6. 1y agodfmsAdds mixed-frequency estimation via quarterly.vars
  7. 1y agorlistingsError and message handling for difftime and zero-row listings
  8. 1y agorlistingsTrueType font support and col_gap in pagination
  9. 2y agorlistingssplit_into_pages_by_var() and pagination moved onto formatters

Frequently asked questions

What is the difference between dfms and rlistings?

They serve adjacent needs but don't currently overlap on shipped themes. dfms and rlistings 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 rlistings?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. dfms and rlistings 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 rlistings?

Top rlistings alternatives in Analytics are ranked by recent ship velocity. Browse the "rlistings alternatives" section above for the current picks, or visit /alternatives/rlistings for the full list with editorial commentary on each.