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dfms vs lobstr

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

dfms vs lobstr: at a glance

Featuredfmslobstr
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesnowcasting, state-space-models, econometrics, ropenscir-lib, introspection, memory, c-api
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 lobstr?

R's object inspector is losing its view of the internals as CRAN closes off the private C API.

lobstr exposes R's internal object representation — sizes, addresses, reference counts, abstract syntax trees. Its two most recent releases are both driven by R's move to a restricted public C API: 1.1.3 stopped reporting a vector's truelength and reworked the reference indicator into refs:n, and 1.2.0 changed what sxp(expand = "environment") shows in order to stay compliant. 1.2.0 also adds src() for exploring srcref objects.

Read the full lobstr trajectory →

dfms vs lobstr: 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.

L
lobstr
ANALYTICS
0.0

R's object inspector is losing its view of the internals as CRAN closes off the private C API.

◆ Current state

lobstr exposes R's internal object representation — sizes, addresses, reference counts, abstract syntax trees. Its two most recent releases are both driven by R's move to a restricted public C API: 1.1.3 stopped reporting a vector's truelength and reworked the reference indicator into refs:n, and 1.2.0 changed what sxp(expand = "environment") shows in order to stay compliant. 1.2.0 also adds src() for exploring srcref objects.

◆ Where it's heading

The package is being rebuilt inside a shrinking window of what R permits. Each release trades some introspection depth for API conformance while trying to keep the diagnostic value intact — showing promise expressions instead of internal frame structures, replacing named with a documented refs scale. Where the constraint does not bite, development continues normally: src() is genuinely new, and the environment-binding fixes remove long-standing errors on for-loop and immediate bindings.

◆ Prediction

Expect further conformance work, since the notes describe it as ongoing, with any remaining non-API-dependent readouts either reworked or dropped as R tightens further.

Alternatives to dfms and lobstr

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 lobstr.

See all dfms alternatives → · See all lobstr alternatives →

Recent activity from dfms and lobstr

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

  1. 1mo agodfmsconvert() exports models to dlm and KFAS state-space objects
  2. 5mo agolobstrNew src() for srcrefs; environment bindings stop erroring
  3. 6mo agodfms1.0: rOpenSci review passed, news decomposition added
  4. 6mo agodfmsMixed-frequency estimation gains AR(1) idiosyncratic errors
  5. 9mo agolobstrtruelength reporting dropped for public C API compliance
  6. 9mo agodfmsC++ compatibility with RcppArmadillo 15.0.2
  7. 1y agodfmsFixes estimation with a single quarterly variable
  8. 1y agodfmsAdds mixed-frequency estimation via quarterly.vars
  9. 4y agolobstrMoves to cpp11, relicensed MIT, adds experimental tree()
  10. 7y agolobstrPROTECT error fixed
  11. 7y agolobstrALTREP sizes computed correctly; obj_addr() stops side-effecting

Frequently asked questions

What is the difference between dfms and lobstr?

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

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

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