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hubPredEvalsData vs revdbayes

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

hubPredEvalsData vs revdbayes: at a glance

FeaturehubPredEvalsDatarevdbayes
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesforecast-evaluation, hubverse, configuration, dashboardsextreme-value-theory, bayesian, rcpp, cran-compliance
Last editorial update1h ago14m ago
WebsiteVisit →Visit →

What is hubPredEvalsData?

The pipeline turning hub forecasts into dashboard-ready evaluation data.

hubPredEvalsData generates the scored evaluation data that hubverse prediction dashboards read, driven by a predevals-config.yml and scoring through hubEvals underneath. It is the youngest package in this part of the stack and the fastest-moving in configuration terms, having already passed a breaking 1.0.0 and a schema-versioned feature addition. Its output contract is a scores.csv file consumed downstream, which shapes what its releases care about.

Read the full hubPredEvalsData trajectory →

What is revdbayes?

Extreme value sampling in pure upkeep mode, mostly answering to Rcpp and CRAN.

revdbayes performs Bayesian extreme value analysis using ratio-of-uniforms sampling, giving random samples rather than MCMC chains. Every entry in the visible window is filed under bug fixes and minor improvements. The most recent, 1.5.7, strips missing values before fitting the generalised Pareto MLE; the two before it are an Rcpp compatibility patch and a response to CRAN check failures that turned out to be false positives.

Read the full revdbayes trajectory →

hubPredEvalsData vs revdbayes: editorial side-by-side

H0.0

The pipeline turning hub forecasts into dashboard-ready evaluation data.

◆ Current state

hubPredEvalsData generates the scored evaluation data that hubverse prediction dashboards read, driven by a predevals-config.yml and scoring through hubEvals underneath. It is the youngest package in this part of the stack and the fastest-moving in configuration terms, having already passed a breaking 1.0.0 and a schema-versioned feature addition. Its output contract is a scores.csv file consumed downstream, which shapes what its releases care about.

◆ Where it's heading

Each release widens what the config file can express — round selection, then scale transformations with per-target overrides, then target labelling pulled from the hub's own task metadata. The pattern is consistent: capability that already exists in hubEvals gets a declarative surface here so hub maintainers configure it rather than write code. Recent attention to byte-stable output ordering shows the file is being treated as a reproducible artifact, not just a report.

◆ Prediction

Expect the config schema to keep absorbing hubEvals capabilities as declarative options, with continued attention to making scores.csv reproducible and diffable between runs.

R
revdbayes
ANALYTICS
0.0

Extreme value sampling in pure upkeep mode, mostly answering to Rcpp and CRAN.

◆ Current state

revdbayes performs Bayesian extreme value analysis using ratio-of-uniforms sampling, giving random samples rather than MCMC chains. Every entry in the visible window is filed under bug fixes and minor improvements. The most recent, 1.5.7, strips missing values before fitting the generalised Pareto MLE; the two before it are an Rcpp compatibility patch and a response to CRAN check failures that turned out to be false positives.

◆ Where it's heading

The methods are settled and the release traffic is external: Rcpp issues, CRAN platform checks, documentation anchor requirements. Two of the six releases exist only because CRAN's check farm flagged something, and one of those flags resolved itself. Sibling package profileCI from the same maintainer has been more active, which suggests attention has moved to newer work rather than away from R entirely.

◆ Prediction

Expect further small releases driven by Rcpp or CRAN check changes rather than by the sampling methods.

Alternatives to hubPredEvalsData and revdbayes

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 hubPredEvalsData or revdbayes.

See all hubPredEvalsData alternatives → · See all revdbayes alternatives →

Recent activity from hubPredEvalsData and revdbayes

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

  1. 1mo agohubPredEvalsDataTarget names pulled from hub metadata; scores.csv made byte-stable
  2. 2mo agohubPredEvalsDataVersioned target data with an as_of column no longer fails scoring
  3. 2mo agohubPredEvalsDataScale transformations become configurable per target
  4. 4mo agohubPredEvalsDataMulti-round hub support via a required rounds_idx property (breaking)
  5. 4mo agorevdbayesMissing values now removed before generalised Pareto MLE fitting
  6. 7mo agorevdbayesRcpp patch applied to avoid masking Rf_error()
  7. 7mo agorevdbayesPatch for macOS CRAN check errors that proved to be false positives
  8. 2y agorevdbayesArgument documentation corrected; Rd link anchors fixed
  9. 2y agorevdbayesRcpp warning fix plus Rd itemize corrections
  10. 2y agorevdbayesC++11 specification dropped to clear a CRAN note

Frequently asked questions

What is the difference between hubPredEvalsData and revdbayes?

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

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

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

What are the best alternatives to revdbayes?

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