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robma vs TidyDensity

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

Shared themes:r-package

robma vs TidyDensity: at a glance

FeaturerobmaTidyDensity
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesr-package, meta-analysis, bayesian, api-redesignstatistical-distributions, random-generation, parameter-estimation, tidyverse
Last editorial update4h ago57m ago
WebsiteVisit →Visit →

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 →

What is TidyDensity?

A distribution catalogue that grows by one family at a time, and rarely breaks anything.

TidyDensity generates tidy-format random data from statistical distributions, with parameter estimation, AIC calculation, summary tables and automatic plotting for each one. Its releases follow a fixed template — breaking changes, new features, minor fixes — and the breaking section is usually empty. Growth comes distribution by distribution: Bernoulli, Burr, triangular, chi-square, zero-truncated negative binomial and others each arrive with a matching set of param_estimate, aic and stats_tbl helpers.

Read the full TidyDensity trajectory →

robma vs TidyDensity: editorial side-by-side

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.

T
TidyDensity
ANALYTICS
0.0

A distribution catalogue that grows by one family at a time, and rarely breaks anything.

◆ Current state

TidyDensity generates tidy-format random data from statistical distributions, with parameter estimation, AIC calculation, summary tables and automatic plotting for each one. Its releases follow a fixed template — breaking changes, new features, minor fixes — and the breaking section is usually empty. Growth comes distribution by distribution: Bernoulli, Burr, triangular, chi-square, zero-truncated negative binomial and others each arrive with a matching set of param_estimate, aic and stats_tbl helpers.

◆ Where it's heading

The package is filling out a matrix rather than changing shape — every new distribution gets the same four or five companion functions, so the surface grows predictably and the design does not. What variation exists comes from utilities that work across distributions: MCMC sampling, bootstrap helpers, time series conversion, distribution comparison. The two genuine breaking changes in this window were both internal reworks, moving generation onto data.table and rewriting quantile normalization for speed.

◆ Prediction

The established pattern of adding a distribution with its full helper set is the most likely continuation. Recent releases have been small, suggesting the catalogue is approaching the distributions its author considers worth covering.

Alternatives to robma and TidyDensity

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 robma or TidyDensity.

See all robma alternatives → · See all TidyDensity alternatives →

Recent activity from robma and TidyDensity

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

  1. 3mo agorobmaUnifies six model constructors into one brma class hierarchy
  2. 8mo agorobmaRoBMA 3.6.1
  3. 11mo agorobmaRoBMA 3.6.0
  4. 11mo agoTidyDensityquantile_normalize rewritten, changing its output
  5. 1y agorobmaRoBMA 3.5.1
  6. 1y agoTidyDensityDocumentation corrections for two distribution functions
  7. 1y agorobmaRoBMA 3.5.0
  8. 1y agorobmaRoBMA 3.4.0
  9. 2y agoTidyDensityZero-truncated distributions and AIC helpers added in bulk
  10. 2y agoTidyDensityMCMC sampling and quantile normalization join the utilities
  11. 2y agoTidyDensityGeneration moves to data.table; native pipe raises the R floor
  12. 2y agoTidyDensityDistributions convertible to time series objects

Frequently asked questions

What is the difference between robma and TidyDensity?

Both compete on the same themes — r-package — within Analytics. robma and TidyDensity 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 robma better than TidyDensity?

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

What are the best alternatives to TidyDensity?

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