nflreadr
The nflverse data loader, whose releases are dictated by the NFL calendar and CRAN's archive policy
Comparison · Analytics
relialearnr vs rfm
A side-by-side editorial comparison of relialearnr and rfm — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-package
relialearnr vs rfm: at a glance
What is relialearnr?
The teaching arm of an R reliability suite keeps pace with whatever its analysis siblings ship.
ReliaLearnR is a set of interactive learnr tutorials for reliability engineering, covering life data analysis, reliability testing, RAM concepts, reliability block diagrams, and repairable systems, each with code exercises and quiz questions. It was WeibullR.learnr until the start of 2026, when the rename and a set of shorter function names arrived together. A companion book now supplements the interactive material.
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.
relialearnr vs rfm: editorial side-by-side
relialearnr
0.0ANALYTICS
The teaching arm of an R reliability suite keeps pace with whatever its analysis siblings ship.
◆ Current state
ReliaLearnR is a set of interactive learnr tutorials for reliability engineering, covering life data analysis, reliability testing, RAM concepts, reliability block diagrams, and repairable systems, each with code exercises and quiz questions. It was WeibullR.learnr until the start of 2026, when the rename and a set of shorter function names arrived together. A companion book now supplements the interactive material.
◆ Where it's heading
The tutorials track the maintainer's analysis packages rather than leading them: repairable systems and mean cumulative function teaching material appeared once the modelling functions for them existed elsewhere in the suite, and the reliability testing tutorial followed the same pattern earlier. Recent work has been about depth rather than coverage — interactive parameter sliders, goodness-of-fit sections, model comparison exercises, more quiz questions per topic. The rename to ReliaLearnR was part of the same suite-wide repositioning away from Weibull-specific branding that the plotting package made.
◆ Prediction
On the established pattern, the next tutorials will follow whatever the analysis packages shipped most recently; the entries do not indicate whether the newer tool-server interfaces will get teaching material of their own.
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 relialearnr 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 relialearnr 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 relialearnr alternatives → · See all rfm alternatives →
Recent activity from relialearnr and rfm
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 2mo agorelialearnrBlock diagram and repairable systems tutorials added
- 3mo agorfmrfm 0.4.0
- 7mo agorelialearnrReliaLearnR 0.3.1
- 7mo agorelialearnrRenamed to ReliaLearnR, with shorter tutorial launchers
- 1y agorelialearnrWeibullR.learnr 0.2.1
- 1y agorelialearnrReliability testing tutorial covering growth analysis and ALT
- 3y agorelialearnrFirst release: the life data analysis tutorial
- 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 relialearnr and rfm?
Both compete on the same themes — r-package — within Analytics. relialearnr and rfm 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 relialearnr better than rfm?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. relialearnr and rfm 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 relialearnr?
Top relialearnr alternatives in Analytics are ranked by recent ship velocity. Browse the "relialearnr alternatives" section above for the current picks, or visit /alternatives/relialearnr 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.