cIRT
A choice-based IRT model published once in 2019 and kept compiling ever since
Comparison · Analytics
DHARMa vs r2dii.analysis
A side-by-side editorial comparison of DHARMa and r2dii.analysis — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-package
DHARMa vs r2dii.analysis: at a glance
What is DHARMa?
DHARMa changed how GLMM residuals are simulated, so the same code now returns different numbers.
DHARMa generates scaled quantile residuals for fitted GLMMs and runs the dispersion, uniformity, and autocorrelation tests built on them. Version 0.5.0 changed the default simulation for hierarchical models from the model's own default, mostly unconditional, to conditional simulation, and states plainly that residuals will differ from those computed by older versions. The same release added brms to the supported model set and reworked how predictors are passed to plotting and testing functions.
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.
DHARMa vs r2dii.analysis: editorial side-by-side
DHARMa
0.0ANALYTICS
DHARMa changed how GLMM residuals are simulated, so the same code now returns different numbers.
◆ Current state
DHARMa generates scaled quantile residuals for fitted GLMMs and runs the dispersion, uniformity, and autocorrelation tests built on them. Version 0.5.0 changed the default simulation for hierarchical models from the model's own default, mostly unconditional, to conditional simulation, and states plainly that residuals will differ from those computed by older versions. The same release added brms to the supported model set and reworked how predictors are passed to plotting and testing functions.
◆ Where it's heading
The package has spent several releases widening which model backends it can diagnose, from glmmTMB through mgcv, phylolm and now brms, while methodological work has gone into handling correlated residuals via the rotation argument. Version 0.5.0 shifts from adding coverage to changing defaults for statistical power. The formula interface arriving across plotResiduals, testCategorical, testQuantiles and the autocorrelation tests suggests the API is being unified rather than extended function by function.
◆ Prediction
The next releases will likely broaden brms support past the simple-model restriction and continue converting remaining functions to the formula interface.
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 DHARMa 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 DHARMa 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 DHARMa alternatives → · See all r2dii.analysis alternatives →
Recent activity from DHARMa and r2dii.analysis
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 2mo agoDHARMaConditional simulation becomes the GLMM default, changing residuals ⚡
- 7mo agor2dii.analysisLow-carbon technology targets filled in for partial company coverage
- 1y agor2dii.analysisColumn definitions filled into the data dictionary
- 1y agor2dii.analysisPackage declared stable, three summarise functions soft-deprecated
- 1y agoDHARMaDHARMa 0.4.7
- 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
- 3y agoDHARMaDHARMa 0.4.6
- 4y agoDHARMaDHARMa 0.4.5
- 4y agoDHARMaDHARMa 0.4.4
- 5y agoDHARMaDHARMa 0.4.3
Frequently asked questions
What is the difference between DHARMa and r2dii.analysis?
Both compete on the same themes — r-package — within Analytics. DHARMa 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 DHARMa better than r2dii.analysis?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. DHARMa 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 DHARMa?
Top DHARMa alternatives in Analytics are ranked by recent ship velocity. Browse the "DHARMa alternatives" section above for the current picks, or visit /alternatives/dharma 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.