tidytlg
A tables-listings-graphs package that reached CRAN and then went quiet.
Comparison · Analytics
dendroNetwork vs dfms
A side-by-side editorial comparison of dendroNetwork and dfms — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:ropensci
dendroNetwork vs dfms: at a glance
What is dendroNetwork?
Six releases, six identical bodies — the feed carries the package abstract instead of release notes
dendroNetwork builds networks of dendrochronological series from similarity between tree-ring measurements, applies community detection to find matching material, and hands the result to Cytoscape for visualisation. That description is all the feed provides: every one of the six visible releases carries the same package abstract as its body, with no record of what changed in any of them. Version 0.5.5 in July 2025 is the most recent.
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.
dendroNetwork vs dfms: editorial side-by-side
dendroNetwork
0.0ANALYTICS
Six releases, six identical bodies — the feed carries the package abstract instead of release notes
◆ Current state
dendroNetwork builds networks of dendrochronological series from similarity between tree-ring measurements, applies community detection to find matching material, and hands the result to Cytoscape for visualisation. That description is all the feed provides: every one of the six visible releases carries the same package abstract as its body, with no record of what changed in any of them. Version 0.5.5 in July 2025 is the most recent.
◆ Where it's heading
What the timestamps show is more informative than the text. Versions 0.5.0 through 0.5.3 were all published within two minutes of each other on 12 April 2024, and in descending version order, which is the signature of a release history backfilled in one pass rather than four separate releases. Real releases follow at 0.5.4 a fortnight later and 0.5.5 fifteen months after that. Development is slow and, on this evidence, undocumented.
◆ Prediction
No prediction is supportable from these entries — none of them describe a change. Any read on where this package is heading would need the NEWS file or the commit history rather than the feed.
dfms
0.0ANALYTICS
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.
Alternatives to dendroNetwork and dfms
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 dendroNetwork or dfms.
Tplyr
Tplyr made clinical summary tables explain where every number came from.
rlistings
Clinical listings that keep inheriting their hardest problem — pagination — from the layer below.
hoardr
A cache-directory helper that has shipped nothing but CRAN-triggered patches for seven years.
gigs
gigs redesigned its whole conversion API for rOpenSci, then spent three releases getting the docs to build.
riem
A weather-data client that keeps rewriting its HTTP layer while slowly tightening its API.
See all dendroNetwork alternatives → · See all dfms alternatives →
Recent activity from dendroNetwork and dfms
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 1mo agodfmsconvert() exports models to dlm and KFAS state-space objects
- 6mo agodfms1.0: rOpenSci review passed, news decomposition added ⚡
- 6mo agodfmsMixed-frequency estimation gains AR(1) idiosyncratic errors
- 9mo agodfmsC++ compatibility with RcppArmadillo 15.0.2
- 1y agodfmsFixes estimation with a single quarterly variable
- 1y agodendroNetworkdendroNetwork 0.5.5
- 1y agodfmsAdds mixed-frequency estimation via quarterly.vars
- 2y agodendroNetworkdendroNetwork 0.5.4
- 2y agodendroNetworkdendroNetwork 0.5.0
- 2y agodendroNetworkdendroNetwork 0.5.1
- 2y agodendroNetworkdendroNetwork 0.5.2
- 2y agodendroNetworkdendroNetwork 0.5.3
Frequently asked questions
What is the difference between dendroNetwork and dfms?
Both compete on the same themes — ropensci — within Analytics. dendroNetwork and dfms 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 dendroNetwork better than dfms?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. dendroNetwork and dfms 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 dendroNetwork?
Top dendroNetwork alternatives in Analytics are ranked by recent ship velocity. Browse the "dendroNetwork alternatives" section above for the current picks, or visit /alternatives/dendronetwork for the full list with editorial commentary on each.
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.