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ageproR vs modeltime.resample

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

ageproR vs modeltime.resample: at a glance

FeatureageproRmodeltime.resample
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesfisheries-science, stock-assessment, r-package, file-format-validationtime series, cross-validation, tidymodels, compatibility maintenance
Last editorial update1h ago5h ago
WebsiteVisit →Visit →

What is ageproR?

ageproR spent two years chasing a moving file format, then added the recruitment models that justify the effort.

An R interface for building and validating AGEPRO input files — the configuration format for a fisheries stock projection program used in stock assessments. Releases come every few months and are dominated by one recurring problem: keeping up with the AGEPRO input file format, which has moved between VERSION 4.0 and VERSION 4.25 in both directions across this window. The package spends considerable effort on validation, version detection, and clear error messages when a file does not match.

Read the full ageproR trajectory →

What is modeltime.resample?

modeltime.resample exists to keep backtesting working as tidymodels shifts underneath it.

modeltime.resample runs time series cross-validation over modeltime models, returning per-resample predictions and accuracy plots. Version 0.3.0 is the substantive release in view: tune 2.0.0 compatibility, deterministic seeding via withr, guaranteed .predictions output, and clearer failures when resample fits break. The three releases before it are dependency chores.

Read the full modeltime.resample trajectory →

ageproR vs modeltime.resample: editorial side-by-side

A
ageproR
ANALYTICS
0.0

ageproR spent two years chasing a moving file format, then added the recruitment models that justify the effort.

◆ Current state

An R interface for building and validating AGEPRO input files — the configuration format for a fisheries stock projection program used in stock assessments. Releases come every few months and are dominated by one recurring problem: keeping up with the AGEPRO input file format, which has moved between VERSION 4.0 and VERSION 4.25 in both directions across this window. The package spends considerable effort on validation, version detection, and clear error messages when a file does not match.

◆ Where it's heading

The version-format churn is settling. Release 0.7.1 reverted the default back to VERSION 4.0 as a bugfix, and 0.9.0 finally set 4.25 as current while retaining a 4.0 compatibility string and improving the detection messages — a resolution rather than another reversal. With that stabilising, the substantive work has been the recruitment model coverage added in 0.8.0, which brought autocorrelated lognormal error structures into the package for the first time. Naming has been converging too, with output_stock_summary and summary_output_flag renamed to auxiliary variants to match the AGEPRO-GUI specification.

◆ Prediction

Expect the remaining recruitment models to be filled in against the AGEPRO specification, and the version handling to stay on 4.25 now that both formats are supported and validated rather than swapped.

M0.0

modeltime.resample exists to keep backtesting working as tidymodels shifts underneath it.

◆ Current state

modeltime.resample runs time series cross-validation over modeltime models, returning per-resample predictions and accuracy plots. Version 0.3.0 is the substantive release in view: tune 2.0.0 compatibility, deterministic seeding via withr, guaranteed .predictions output, and clearer failures when resample fits break. The three releases before it are dependency chores.

◆ Where it's heading

Every entry here is compatibility work against something upstream — hardhat 1.0.0, workflows regression mode, then tune 2.0.0 twice. The 0.3.0 notes show a second concern emerging alongside it: making failures legible, with .notes on failed fits, actionable errors from unnest_modeltime_resamples(), and fallback logic when prediction columns go missing across versions. Reproducibility gets the same treatment through explicit seeding.

◆ Prediction

Expect the next release to track the next tidymodels breaking change, with any new work continuing on error reporting rather than resampling strategies.

Alternatives to ageproR and modeltime.resample

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 ageproR or modeltime.resample.

See all ageproR alternatives → · See all modeltime.resample alternatives →

Recent activity from ageproR and modeltime.resample

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

  1. 2mo agoageproRwrite_inp option flag detection fixed after 0.8.0 dependency changes
  2. 6mo agoageproRAGEPRO VERSION 4.25 becomes the default format, with 4.0 kept compatible
  3. 11mo agomodeltime.resampletune 2.0 support, deterministic seeding, clearer errors
  4. 11mo agomodeltime.resampleDependency cleanup ahead of the next tune release
  5. 1y agoageproRFour recruitment models added, including autocorrelated lognormal error
  6. 1y agoageproRagepro_inp_model initialisation aligned with the other model classes
  7. 1y agoageproRVersion string read from line 1; invalid recruitment data blocks export
  8. 1y agoageproRInput file format reverted to VERSION 4.0 as a bugfix
  9. 3y agomodeltime.resampleFixes workflows in regression mode
  10. 4y agomodeltime.resampleUpdates for hardhat 1.0.0

Frequently asked questions

What is the difference between ageproR and modeltime.resample?

They serve adjacent needs but don't currently overlap on shipped themes. ageproR and modeltime.resample 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 ageproR better than modeltime.resample?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. ageproR and modeltime.resample 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 ageproR?

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

What are the best alternatives to modeltime.resample?

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