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Comparison · Analytics

healthyR.ts vs robma

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

healthyR.ts vs robma: at a glance

FeaturehealthyR.tsrobma
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themestime series, healthyverse, stationarity, ggplot2r-package, meta-analysis, bayesian, api-redesign
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 robma?

RoBMA 4.0 tears out its own constructor surface and rebuilds on one class hierarchy

RoBMA fits robust Bayesian model-averaged meta-analyses that adjust for publication bias. The 3.x line grew by accretion: separate constructors for each model family (RoBMA.reg, NoBMA, BiBMA and their .reg variants), a spike-and-slab algorithm in 3.3.0 that made estimation fast enough to matter, then a steady stream of post-estimation tooling gated on that algorithm — heterogeneity summaries, residuals, funnel plots, z-curve conversion, predict, extract, pooled and adjusted effects. Version 4.0.0 in May 2026 collapses all of it into a unified brma class hierarchy.

Read the full robma trajectory →

healthyR.ts vs robma: 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
robma
ANALYTICS
0.0

RoBMA 4.0 tears out its own constructor surface and rebuilds on one class hierarchy

◆ Current state

RoBMA fits robust Bayesian model-averaged meta-analyses that adjust for publication bias. The 3.x line grew by accretion: separate constructors for each model family (RoBMA.reg, NoBMA, BiBMA and their .reg variants), a spike-and-slab algorithm in 3.3.0 that made estimation fast enough to matter, then a steady stream of post-estimation tooling gated on that algorithm — heterogeneity summaries, residuals, funnel plots, z-curve conversion, predict, extract, pooled and adjusted effects. Version 4.0.0 in May 2026 collapses all of it into a unified brma class hierarchy.

◆ Where it's heading

The 3.x series solved the modeling problem and left an interface problem behind: a caller had to know which of six constructors matched their data type, and argument names differed across them. 4.0.0 resolves that by making the model family a set of arguments rather than a function name, and by standardizing input naming on metafor-style conventions. It shipped one day after BayesTools 0.3.0, the author's own upstream infrastructure package, whose new standardization and prior-transformation machinery this rewrite depends on.

◆ Prediction

A rewrite this wide usually needs a follow-up, so expect 4.0.x patches addressing migration gaps as users hit the removed constructors and renamed arguments.

Alternatives to healthyR.ts and robma

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 robma.

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

Recent activity from healthyR.ts and robma

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

  1. 3mo agorobmaUnifies six model constructors into one brma class hierarchy
  2. 6mo agohealthyR.tsRandom walk plot added; ts_ma_plot drops xts for ggplot2 facets
  3. 8mo agorobmaRoBMA 3.6.1
  4. 11mo agorobmaRoBMA 3.6.0
  5. 1y agorobmaRoBMA 3.5.1
  6. 1y agorobmaRoBMA 3.5.0
  7. 1y agorobmaRoBMA 3.4.0
  8. 1y agohealthyR.tsInvisible returns dropped; random walk and vva plot fixes
  9. 2y agohealthyR.tsFive log and differencing transform utilities added
  10. 2y agohealthyR.tsStationarity testing and auto_stationarize added
  11. 2y agohealthyR.tsSingle example fix
  12. 3y agohealthyR.tsBoilerplate fitting uses show_best directly

Frequently asked questions

What is the difference between healthyR.ts and robma?

They serve adjacent needs but don't currently overlap on shipped themes. healthyR.ts and robma 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 robma?

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

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