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healthyR.ts vs rfm

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

healthyR.ts vs rfm: at a glance

FeaturehealthyR.tsrfm
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themestime series, healthyverse, stationarity, ggplot2r-package, customer-analytics, segmentation, dependencies
Last editorial update49m ago2h ago
WebsiteVisit →Visit →

What is healthyR.ts?

healthyR.ts keeps adding time-series helpers, then quietly breaks the old ones to modernise them.

A time-series companion in the healthyverse family, shipping helper functions in batches: growth-rate vectors, an ADF test and auto_stationarize() in 0.2.11, then five log and differencing transforms in 0.3.0, and a random-walk plot in 0.3.2. Alongside the additions runs a steady stream of breaking cleanups — invisible returns dropped, R 4.1 required for the native pipe, and ts_ma_plot() refactored onto ggplot2 facets with its xts output removed and its return value cut from six items to two.

Read the full healthyR.ts trajectory →

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.

Read the full rfm trajectory →

healthyR.ts vs rfm: editorial side-by-side

H
healthyR.ts
ANALYTICS
0.0

healthyR.ts keeps adding time-series helpers, then quietly breaks the old ones to modernise them.

◆ Current state

A time-series companion in the healthyverse family, shipping helper functions in batches: growth-rate vectors, an ADF test and auto_stationarize() in 0.2.11, then five log and differencing transforms in 0.3.0, and a random-walk plot in 0.3.2. Alongside the additions runs a steady stream of breaking cleanups — invisible returns dropped, R 4.1 required for the native pipe, and ts_ma_plot() refactored onto ggplot2 facets with its xts output removed and its return value cut from six items to two.

◆ Where it's heading

Two threads, both consistent. The functional one is coverage of the stationarity workflow — transform, test, auto-stationarize, plot — assembled function by function rather than as a single API. The structural one is convergence on ggplot2 and tidy conventions, retiring xts objects and multi-object return lists as it goes. The package is not afraid to break return shapes to get there, so upgrades are not drop-in.

◆ Prediction

Expect the remaining functions that still return xts objects or bundled lists to get the same ggplot2-only treatment, since ts_ma_plot() was refactored on exactly that rationale.

R
rfm
ANALYTICS
0.0

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 healthyR.ts 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 healthyR.ts or rfm.

See all healthyR.ts alternatives → · See all rfm alternatives →

Recent activity from healthyR.ts and rfm

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

  1. 3mo agorfmrfm 0.4.0
  2. 6mo agohealthyR.tsRandom walk plot added; ts_ma_plot drops xts for ggplot2 facets
  3. 1y agohealthyR.tsInvisible returns dropped; random walk and vva plot fixes
  4. 2y agohealthyR.tsFive log and differencing transform utilities added
  5. 2y agohealthyR.tsStationarity testing and auto_stationarize added
  6. 2y agohealthyR.tsSingle example fix
  7. 3y agohealthyR.tsBoilerplate fitting uses show_best directly
  8. 6y agorfmrfm 0.2.2
  9. 6y agorfmrfm 0.2.1
  10. 7y agorfmrfm 0.2.0
  11. 8y agorfmrfm 0.1.1
  12. 8y agorfmrfm 0.1.0

Frequently asked questions

What is the difference between healthyR.ts and rfm?

They serve adjacent needs but don't currently overlap on shipped themes. healthyR.ts 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 healthyR.ts better than rfm?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. healthyR.ts 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 healthyR.ts?

Top healthyR.ts alternatives in Analytics are ranked by recent ship velocity. Browse the "healthyR.ts alternatives" section above for the current picks, or visit /alternatives/healthyr-ts 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.