cIRT
A choice-based IRT model published once in 2019 and kept compiling ever since
Comparison · Analytics
BORG vs r2dii.analysis
A side-by-side editorial comparison of BORG and r2dii.analysis — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-package
BORG vs r2dii.analysis: at a glance
What is BORG?
A cross-validation guard that refuses to run random CV on dependent data unless you insist
BORG detects spatial, temporal and clustered dependence in a modelling dataset and generates a cross-validation scheme that respects it — spatial blocks, temporal blocks, group folds — rather than letting random splits leak information between train and test. Its distinguishing choice is enforcement: when it finds dependence, random CV is blocked outright and needs an explicit allow_random=TRUE to proceed. The package also wraps the standard rsample and caret entry points so the guard applies inside existing workflows.
What is r2dii.analysis?
The climate-alignment maths behind PACTA, now stable and maintained rather than reshaped
r2dii.analysis computes the target-setting side of PACTA: market-share and sectoral decarbonisation targets that measure a loan book or portfolio against climate scenarios. It sits downstream of the matched company data the sibling packages produce. The 0.5.0 release declared it lifecycle-stable and handed maintenance to a new lead, and releases since have been narrow corrections rather than new methods.
BORG vs r2dii.analysis: editorial side-by-side
BORG
0.0ANALYTICS
A cross-validation guard that refuses to run random CV on dependent data unless you insist
◆ Current state
BORG detects spatial, temporal and clustered dependence in a modelling dataset and generates a cross-validation scheme that respects it — spatial blocks, temporal blocks, group folds — rather than letting random splits leak information between train and test. Its distinguishing choice is enforcement: when it finds dependence, random CV is blocked outright and needs an explicit allow_random=TRUE to proceed. The package also wraps the standard rsample and caret entry points so the guard applies inside existing workflows.
◆ Where it's heading
The entire visible history is a single day, and the sequence within it is coherent rather than churn: enforcement first, then the evidence layer, then framework integration, then idiomatic R polish. The evidence work matters to the pitch — borg_compare_cv() runs random against blocked CV so users see the inflation on their own data instead of taking the warning on faith, and the methods-text and certificate exports are aimed squarely at getting this into published papers. By the final release the interface has been rebuilt on standard S3 plot and summary methods.
◆ Prediction
The wrappers so far cover rsample and caret; tidymodels and mlr3 are the obvious remaining entry points if the guard is to reach the workflows it hasn't yet intercepted.
r2dii.analysis
0.0ANALYTICS
The climate-alignment maths behind PACTA, now stable and maintained rather than reshaped
◆ Current state
r2dii.analysis computes the target-setting side of PACTA: market-share and sectoral decarbonisation targets that measure a loan book or portfolio against climate scenarios. It sits downstream of the matched company data the sibling packages produce. The 0.5.0 release declared it lifecycle-stable and handed maintenance to a new lead, and releases since have been narrow corrections rather than new methods.
◆ Where it's heading
The history is a package converging. Early releases churn the output contract of target_market_share() and target_sda() — which sectors appear, which years, how missing production is treated — and each change alters the numbers users get. The ald-to-abcd rename runs across several releases before completing, and by 0.5.0 the churn has stopped, with three older summarise functions soft-deprecated and the package marked stable. What remains is edge-case correctness in target coverage.
◆ Prediction
With the package marked stable and the terminology migration finished, the soft-deprecated summarise functions are the obvious next thing to remove outright.
Alternatives to BORG and r2dii.analysis
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 BORG or r2dii.analysis.
MetaboAnalystR
The R engine behind MetaboAnalyst closes the gap from raw spectra to biological interpretation
fmtr
Rebuilding SAS's formatting layer in R, one format specification at a time
betaselectr
Standardised coefficients for models where standardising everything is wrong — but the feed only links out
SSN2
Stream-network spatial models learning to run on data that no longer fits in memory
BiocManager
Bioconductor's installer, frozen at 1.30.x and tuned almost entirely through environment variables
See all BORG alternatives → · See all r2dii.analysis alternatives →
Recent activity from BORG and r2dii.analysis
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 7mo agor2dii.analysisLow-carbon technology targets filled in for partial company coverage
- 7mo agoBORGInterface rebuilt on standard S3 plot and summary methods
- 7mo agoBORGGuarded wrappers for rsample and caret splitting functions
- 7mo agoBORGEmpirical inflation comparison and publication-ready reporting
- 7mo agoBORGRandom CV blocked by default when dependence is detected ⚡
- 7mo agoBORGVersion bump to 0.1.1
- 1y agor2dii.analysisColumn definitions filled into the data dictionary
- 1y agor2dii.analysisPackage declared stable, three summarise functions soft-deprecated
- 2y agor2dii.analysisald argument removed for good in favour of abcd
- 2y agor2dii.analysisCompany-level SDA converges on the scenario's final year
- 3y agor2dii.analysisRepository moved to the RMI-PACTA organisation
Frequently asked questions
What is the difference between BORG and r2dii.analysis?
Both compete on the same themes — r-package — within Analytics. BORG and r2dii.analysis 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 BORG better than r2dii.analysis?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. BORG and r2dii.analysis 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 BORG?
Top BORG alternatives in Analytics are ranked by recent ship velocity. Browse the "BORG alternatives" section above for the current picks, or visit /alternatives/borg for the full list with editorial commentary on each.
What are the best alternatives to r2dii.analysis?
Top r2dii.analysis alternatives in Analytics are ranked by recent ship velocity. Browse the "r2dii.analysis alternatives" section above for the current picks, or visit /alternatives/r2dii-analysis for the full list with editorial commentary on each.