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ageproR vs spmodel

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

Shared themes:r-package

ageproR vs spmodel: at a glance

FeatureageproRspmodel
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesfisheries-science, stock-assessment, r-package, file-format-validationspatial-statistics, regression-modelling, kriging, r-package
Last editorial update57m 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 spmodel?

Spatial regression in R, adding block kriging and then tuning the numerics underneath it

spmodel fits spatial linear and generalised linear models, for both point-referenced and areal data, with prediction and diagnostics attached. Block prediction arrived in 0.11.0 and the releases since have refined it. The most recent release changes optimiser behaviour: the default Nelder-Mead relative stopping tolerance tightens from 1e-4 to 1e-6 to reduce convergence on local rather than global maxima.

Read the full spmodel trajectory →

ageproR vs spmodel: 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.

S
spmodel
ANALYTICS
0.0

Spatial regression in R, adding block kriging and then tuning the numerics underneath it

◆ Current state

spmodel fits spatial linear and generalised linear models, for both point-referenced and areal data, with prediction and diagnostics attached. Block prediction arrived in 0.11.0 and the releases since have refined it. The most recent release changes optimiser behaviour: the default Nelder-Mead relative stopping tolerance tightens from 1e-4 to 1e-6 to reduce convergence on local rather than global maxima.

◆ Where it's heading

Two threads run in parallel. The first is expanding what can be predicted — point predictions, then areal averages over a region via block kriging, then better accuracy and efficiency for that path as the block size default moved from 1000 to 4000 in 0.12.0. The second is numerical trustworthiness, and it is unusually prominent here: a range-constraint option for stability in 0.9.0, a corrected log determinant of the fixed effects in the restricted log likelihood in 0.11.0, a cloud semivariogram that had been doubling the semivariance fixed in 0.11.1, and now a tighter optimiser tolerance. Several of these silently changed results before they were caught.

◆ Prediction

Expect the maintainers to keep publishing explicit reproduction instructions alongside numerical default changes, as 0.13.0 does by documenting the `control = list(reltol = 1e-4)` escape hatch. The entries give no signal of expansion beyond the current model families.

Alternatives to ageproR and spmodel

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 spmodel.

See all ageproR alternatives → · See all spmodel alternatives →

Recent activity from ageproR and spmodel

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

  1. 2mo agospmodelTighter optimiser tolerance to avoid local maxima
  2. 2mo agoageproRwrite_inp option flag detection fixed after 0.8.0 dependency changes
  3. 6mo agoageproRAGEPRO VERSION 4.25 becomes the default format, with 4.0 kept compatible
  4. 6mo agospmodelEmpirical autocovariance function and better block kriging accuracy
  5. 9mo agospmodelCloud semivariogram doubling fixed; geometry warnings added
  6. 1y agoageproRFour recruitment models added, including autocorrelated lognormal error
  7. 1y agospmodelBlock kriging for areal averages and their uncertainty
  8. 1y agoageproRagepro_inp_model initialisation aligned with the other model classes
  9. 1y agospmodelRobust semivariogram and new covariance types for areal models
  10. 1y agospmodelRange constraint option and redefined covariance type names
  11. 1y agoageproRVersion string read from line 1; invalid recruitment data blocks export
  12. 1y agoageproRInput file format reverted to VERSION 4.0 as a bugfix

Frequently asked questions

What is the difference between ageproR and spmodel?

Both compete on the same themes — r-package — within Analytics. ageproR and spmodel 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 spmodel?

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

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