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dfms vs r2rtf

A side-by-side editorial comparison of dfms and r2rtf — release velocity, themes, recent moves, and the top alternatives to consider.

dfms vs r2rtf: at a glance

Featuredfmsr2rtf
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesnowcasting, state-space-models, econometrics, ropensciclinical-reporting, rtf, internationalization, document-conversion
Last editorial update4h ago1h 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 r2rtf?

The clinical-report table engine learned Chinese, then learned to leave RTF entirely

r2rtf builds the RTF tables, listings and figures that go into clinical study reports, and its recent releases have been about widening who and what it can serve rather than changing how tables are composed. The 1.2.0 release added internationalization — a SimSun font path for Chinese characters plus hyphenation control — and 1.3.0 followed with write_docx() and write_html(), turning the LibreOffice conversion the package had documented into exported functions.

Read the full r2rtf trajectory →

dfms vs r2rtf: 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
r2rtf
ANALYTICS
0.0

The clinical-report table engine learned Chinese, then learned to leave RTF entirely

◆ Current state

r2rtf builds the RTF tables, listings and figures that go into clinical study reports, and its recent releases have been about widening who and what it can serve rather than changing how tables are composed. The 1.2.0 release added internationalization — a SimSun font path for Chinese characters plus hyphenation control — and 1.3.0 followed with write_docx() and write_html(), turning the LibreOffice conversion the package had documented into exported functions.

◆ Where it's heading

Two threads run through the window. One is output reach: RTF remains the composition target, but the artifacts that come out of it now include DOCX and HTML, and page numbering can be made table-relative across multi-page tables. The other is durability under a moving R and font stack — the ANSI/Unicode converter was rebuilt, the LaTeX mapping table generated from code rather than shipped as sysdata, unlist() usage fixed for R 4.5, and graphics-device leaks that produced stray Rplots.pdf closed off.

◆ Prediction

Having exported DOCX and HTML conversion, the likely next step is filling in what those formats lose relative to RTF — pagination and footnote fidelity are the obvious gaps. The i18n path currently covers Chinese only, so additional font families are the other plausible direction.

Alternatives to dfms and r2rtf

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 r2rtf.

See all dfms alternatives → · See all r2rtf alternatives →

Recent activity from dfms and r2rtf

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. 7mo agor2rtfDOCX and HTML output become exported functions
  5. 9mo agodfmsC++ compatibility with RcppArmadillo 15.0.2
  6. 11mo agor2rtfChinese character support arrives via an i18n font path
  7. 1y agodfmsFixes estimation with a single quarterly variable
  8. 1y agodfmsAdds mixed-frequency estimation via quarterly.vars
  9. 1y agor2rtfText colour fixed for figures encoded into RTF
  10. 1y agor2rtfFootnote handling fixed for R 4.5.0
  11. 1y agor2rtfUnicode converter rebuilt and mapping table made inspectable
  12. 2y agor2rtfUTF-8 conversion fix and LibreOffice 7.6 support

Frequently asked questions

What is the difference between dfms and r2rtf?

They serve adjacent needs but don't currently overlap on shipped themes. dfms and r2rtf 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 r2rtf?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. dfms and r2rtf 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 r2rtf?

Top r2rtf alternatives in Analytics are ranked by recent ship velocity. Browse the "r2rtf alternatives" section above for the current picks, or visit /alternatives/r2rtf for the full list with editorial commentary on each.