nflreadr
The nflverse data loader, whose releases are dictated by the NFL calendar and CRAN's archive policy
Comparison · Analytics
fitVARMxID vs rfm
A side-by-side editorial comparison of fitVARMxID and rfm — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-package
fitVARMxID vs rfm: at a glance
What is fitVARMxID?
A VAR-model fitting package acquiring the standard R methods it launched without
fitVARMxID fits vector autoregressive models via OpenMx identification, and is one of several packages maintained by the jeksterslab account. Its recent releases are small and additive: confint() and plot() methods, a save function, and before that a documentation pass. The feed also carries automated build commits that are pure CI artifacts.
What is rfm?
A customer segmentation package that went quiet for six years and returned with dependency hygiene
rfm computes recency, frequency and monetary segmentation for customer analytics in R. The feature surface was set early: 0.1.0 shipped a Shiny app and customer-level input, 0.2.0 added default segments and median statistics, 0.2.1 added user-specified score thresholds and returnable plot objects. Then nothing for nearly six years. Version 0.4.0 in April 2026 fixes a missing-column error and a customer id fault, and moves plotly and gganimate from Suggests to Imports.
fitVARMxID vs rfm: editorial side-by-side
fitVARMxID
2.5ANALYTICS
A VAR-model fitting package acquiring the standard R methods it launched without
◆ Current state
fitVARMxID fits vector autoregressive models via OpenMx identification, and is one of several packages maintained by the jeksterslab account. Its recent releases are small and additive: confint() and plot() methods, a save function, and before that a documentation pass. The feed also carries automated build commits that are pure CI artifacts.
◆ Where it's heading
This is a package settling into R conventions rather than growing capability. Adding confint() and plot() is the standard-methods work most modeling packages do once the estimation core is stable — it signals the author considers the fitting side done. Cadence is roughly quarterly and the changes get smaller each time.
◆ Prediction
Further method coverage — summary(), predict(), or coef() — is the likely next step, since confint() and plot() are usually the first two of that set rather than the last.
rfm
0.0ANALYTICS
A customer segmentation package that went quiet for six years and returned with dependency hygiene
◆ Current state
rfm computes recency, frequency and monetary segmentation for customer analytics in R. The feature surface was set early: 0.1.0 shipped a Shiny app and customer-level input, 0.2.0 added default segments and median statistics, 0.2.1 added user-specified score thresholds and returnable plot objects. Then nothing for nearly six years. Version 0.4.0 in April 2026 fixes a missing-column error and a customer id fault, and moves plotly and gganimate from Suggests to Imports.
◆ Where it's heading
The 0.4.0 release says more about maintenance posture than about product direction — the version jump past 0.3.x with only two bug fixes and a dependency reshuffle suggests a package being brought back to a releasable state rather than resuming development. Promoting plotly and gganimate to Imports makes the visualization stack mandatory, which is a heavier install in exchange for a simpler code path. The core RFM computation itself has not changed in this window.
◆ Prediction
The entries show a package returning from dormancy rather than pursuing a roadmap, so further small fixes are more likely than new segmentation capability.
Alternatives to fitVARMxID and rfm
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 fitVARMxID or rfm.
susier
Fine-mapping workhorse susieR spends its releases hunting null-effect trimming bugs
UCell
A rank-based gene signature scorer that has grown by adapting to whatever object format single-cell R uses next
detectseparation
A diagnostic package that generalized past its own name, then learned to say which kind of separation it found
brglm2
A bias-reduction package reaches 1.0 by adding an estimator built for high-dimensional logistic regression
bayestools
The JAGS toolkit under RoBMA, shipping the standardization machinery its downstream rewrite needed
See all fitVARMxID alternatives → · See all rfm alternatives →
Recent activity from fitVARMxID and rfm
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 15d agofitVARMxIDfitVARMxID 1.0.5
- 3mo agorfmrfm 0.4.0
- 4mo agofitVARMxIDfitVARMxID 1.0.3
- 5mo agofitVARMxIDv1.0.2: Automated build [skip ci].
- 6y agorfmrfm 0.2.2
- 6y agorfmrfm 0.2.1
- 7y agorfmrfm 0.2.0
- 8y agorfmrfm 0.1.1
- 8y agorfmrfm 0.1.0
Frequently asked questions
What is the difference between fitVARMxID and rfm?
Both compete on the same themes — r-package — within Analytics. fitVARMxID is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.
Is fitVARMxID better than rfm?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. fitVARMxID is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.
What are the best alternatives to fitVARMxID?
Top fitVARMxID alternatives in Analytics are ranked by recent ship velocity. Browse the "fitVARMxID alternatives" section above for the current picks, or visit /alternatives/fitvarmxid for the full list with editorial commentary on each.
What are the best alternatives to rfm?
Top rfm alternatives in Analytics are ranked by recent ship velocity. Browse the "rfm alternatives" section above for the current picks, or visit /alternatives/rfm for the full list with editorial commentary on each.