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charlatan vs RBesT

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

charlatan vs RBesT: at a glance

FeaturecharlatanRBesT
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesfake-data, r-package, ropensci, localesbayesian-statistics, clinical-trials, stan, r-language
Last editorial update3h ago42m ago
WebsiteVisit →Visit →

What is charlatan?

R's fake-data generator rebuilt its provider hierarchy so contributors can add one locale without touching the rest.

charlatan generates realistic fake data — names, addresses, phone numbers, jobs, internet artefacts — across many locales, following the same model as faker in Python and Perl. The 0.6.1 release reworked the provider class hierarchy so locale-specific providers inherit from a parent, and 0.6.2 since has been a documentation rebuild that happened to surface a duplicate Norwegian phone number pattern. Activity is sparse and bursty.

Read the full charlatan trajectory →

What is RBesT?

RBesT is teaching its Bayesian decision rules to answer two-sided questions.

RBesT builds meta-analytic-predictive priors — the machinery for borrowing historical control data into a new trial — and evaluates the operating characteristics of decisions made with them. The stable line has spent several releases on effective sample size: ESS for normal mixtures via a new `family` argument, boundary corrections when no responses or no non-responses are observed, and stabilised ELIR computations. The 1.9-0 release candidate extends the normal, binomial and Poisson outcome functions to two-sided decisions.

Read the full RBesT trajectory →

charlatan vs RBesT: editorial side-by-side

C
charlatan
ANALYTICS
0.0

R's fake-data generator rebuilt its provider hierarchy so contributors can add one locale without touching the rest.

◆ Current state

charlatan generates realistic fake data — names, addresses, phone numbers, jobs, internet artefacts — across many locales, following the same model as faker in Python and Perl. The 0.6.1 release reworked the provider class hierarchy so locale-specific providers inherit from a parent, and 0.6.2 since has been a documentation rebuild that happened to surface a duplicate Norwegian phone number pattern. Activity is sparse and bursty.

◆ Where it's heading

The package's value scales with locale coverage, and its releases track that: early versions added data-type providers, middle versions added locales one contributor at a time, and 0.6.1 attacked the bottleneck by restructuring the class hierarchy so a locale can override a single function. Development has effectively been handed to contributors, with maintainer releases reduced to docs rebuilds and CRAN compliance.

◆ Prediction

Expect the next substantive release to be an accumulation of contributed locales and providers arriving through the new parent-provider structure, rather than maintainer-driven feature work.

R
RBesT
ANALYTICS
0.0

RBesT is teaching its Bayesian decision rules to answer two-sided questions.

◆ Current state

RBesT builds meta-analytic-predictive priors — the machinery for borrowing historical control data into a new trial — and evaluates the operating characteristics of decisions made with them. The stable line has spent several releases on effective sample size: ESS for normal mixtures via a new `family` argument, boundary corrections when no responses or no non-responses are observed, and stabilised ELIR computations. The 1.9-0 release candidate extends the normal, binomial and Poisson outcome functions to two-sided decisions.

◆ Where it's heading

Two currents run through the changelog. One is ESS hardening — nearly every release since 1.7-4 fixes another edge case where the ELIR calculation aborted or returned something unstable, which is what happens when a quantity used to justify prior strength to regulators gets scrutinised. The other is Stan and brms integration debt: array syntax updates, a minimum Stan version bump, truncated prior generation for `mixstanvar`, deterministic EM. The RC's contributor list shows a second active maintainer, and the work is broader than any recent stable release.

◆ Prediction

The release candidate covers all three outcome families and has already absorbed a round of review comments, so the next step is most likely the 1.9-0 CRAN release itself rather than further feature work.

Alternatives to charlatan and RBesT

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 charlatan or RBesT.

See all charlatan alternatives → · See all RBesT alternatives →

Recent activity from charlatan and RBesT

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

  1. 5mo agoRBesTTwo-sided decisions across normal, binomial and Poisson outcomes
  2. 7mo agocharlatanDocs rebuild surfaces a duplicate Norwegian phone pattern
  3. 1y agoRBesTJSON read and write for mixture objects
  4. 1y agoRBesTess() fixed inside apply functions
  5. 1y agoRBesTESS for normal mixtures in the exponential family
  6. 1y agoRBesTTruncated mixture priors for brms, plus faster Stan models
  7. 1y agocharlatanProvider classes restructured so locales can override single functions
  8. 2y agoRBesTStan array syntax update and CRAN system requirements
  9. 6y agocharlatanNew locales and providers; allowed_locales() added
  10. 7y agocharlatanLocale naming standardised; French and Danish data corrected
  11. 8y agocharlatancharlatan v0.2.2
  12. 8y agocharlatanSix new providers broaden charlatan beyond names and addresses

Frequently asked questions

What is the difference between charlatan and RBesT?

They serve adjacent needs but don't currently overlap on shipped themes. charlatan and RBesT 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 charlatan better than RBesT?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. charlatan and RBesT 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 charlatan?

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

What are the best alternatives to RBesT?

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