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hubEvals vs tidycmprsk

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

Shared themes:r-package

hubEvals vs tidycmprsk: at a glance

FeaturehubEvalstidycmprsk
SectorAnalyticsAnalytics
Velocity score2.50.0
Sparks · 30d00
Top themesforecast-evaluation, scoring, epidemiology, r-packagecompeting-risks, survival-analysis, tidyverse, gtsummary
Last editorial update1h ago45m ago
WebsiteVisit →Visit →

What is hubEvals?

Forecast-hub scoring that learned to handle joint, sample-based predictions.

hubEvals scores model output from collaborative forecasting hubs, wrapping scoringutils and translating hubverse formats into forecast objects it can evaluate. The package has moved quickly from a thin translation layer to something that handles every output type the hubverse defines — quantile, mean, median, nominal and ordinal pmf, and samples. The most recent releases are almost entirely about the failure modes of relative skill scoring rather than about new metrics.

Read the full hubEvals trajectory →

What is tidycmprsk?

Competing-risks modelling that now moves only when its neighbours do.

tidycmprsk wraps competing risks regression and cumulative incidence estimation in tidy-style output, so results slot into gtsummary tables and ggsurvfit plots. The last two releases are small: 1.1.2 sorts tidy.tidycuminc() output by stratum, 1.1.1 is an HTML5 documentation update for CRAN. The substantive work in the window is 1.1.0, which reorganised the gtsummary relationship.

Read the full tidycmprsk trajectory →

hubEvals vs tidycmprsk: editorial side-by-side

H
hubEvals
ANALYTICS
2.5

Forecast-hub scoring that learned to handle joint, sample-based predictions.

◆ Current state

hubEvals scores model output from collaborative forecasting hubs, wrapping scoringutils and translating hubverse formats into forecast objects it can evaluate. The package has moved quickly from a thin translation layer to something that handles every output type the hubverse defines — quantile, mean, median, nominal and ordinal pmf, and samples. The most recent releases are almost entirely about the failure modes of relative skill scoring rather than about new metrics.

◆ Where it's heading

Two threads dominate. The first is coverage of output types, which reached its widest point with sample-based and compound scoring. The second, and the one occupying every recent release, is making relative skill degrade gracefully: single-model input, comparison groups with one model, and groups missing the requested baseline have each been converted from a cryptic upstream abort into a defined result. That pattern — inherited scoringutils errors being caught and given hub-specific meaning — is the clearest signal of where this package adds value.

◆ Prediction

Expect continued work smoothing scoringutils error surfaces into hub-aware behaviour, and performance attention on relative skill, which was explicitly optimised in the latest release.

T
tidycmprsk
ANALYTICS
0.0

Competing-risks modelling that now moves only when its neighbours do.

◆ Current state

tidycmprsk wraps competing risks regression and cumulative incidence estimation in tidy-style output, so results slot into gtsummary tables and ggsurvfit plots. The last two releases are small: 1.1.2 sorts tidy.tidycuminc() output by stratum, 1.1.1 is an HTML5 documentation update for CRAN. The substantive work in the window is 1.1.0, which reorganised the gtsummary relationship.

◆ Where it's heading

The package has spent its releases handing responsibilities to neighbouring packages rather than growing its own surface. Plotting was deprecated then made defunct in favour of ggsurvfit::ggcuminc(), and 1.1.0 moved the regression table methods so that gtsummary could drop tidycmprsk as a dependency. What remains is the estimation core plus the S3 methods that let other packages consume it, which is a deliberate narrowing.

◆ Prediction

Expect releases to continue tracking changes in gtsummary and the broader tidy survival stack rather than adding estimation features.

Alternatives to hubEvals and tidycmprsk

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 hubEvals or tidycmprsk.

See all hubEvals alternatives → · See all tidycmprsk alternatives →

Recent activity from hubEvals and tidycmprsk

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

  1. 24d agohubEvalsScored-forecast counts and faster relative skill
  2. 1mo agohubEvalsDisaggregated relative skill no longer aborts the whole call
  3. 1mo agohubEvalsSingle-model scoring returns relative skill of 1 instead of erroring
  4. 4mo agotidycmprsktidycmprsk 1.1.2
  5. 5mo agohubEvalsSample output types and multivariate compound scoring
  6. 6mo agohubEvalsScoring on transformed scales via transform arguments
  7. 9mo agotidycmprsktidycmprsk 1.1.1
  8. 11mo agohubEvalsFirst release: score_model_out() and the scoringutils bridge
  9. 1y agotidycmprsktidycmprsk 1.1.0
  10. 2y agotidycmprsktidycmprsk 1.0.0
  11. 3y agotidycmprsktidycmprsk 0.2.0
  12. 4y agotidycmprsktidycmprsk 0.1.2

Frequently asked questions

What is the difference between hubEvals and tidycmprsk?

Both compete on the same themes — r-package — within Analytics. hubEvals is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.

Is hubEvals better than tidycmprsk?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. hubEvals is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.

What are the best alternatives to hubEvals?

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

What are the best alternatives to tidycmprsk?

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