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MultiSpline vs r2dii.analysis

A side-by-side editorial comparison of MultiSpline and r2dii.analysis — release velocity, themes, recent moves, and the top alternatives to consider.

Shared themes:r-package

MultiSpline vs r2dii.analysis: at a glance

FeatureMultiSpliner2dii.analysis
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themessplines, multilevel-models, longitudinal-data, r-packageclimate-finance, portfolio-alignment, pacta, scenario-analysis
Last editorial update1h ago18m ago
WebsiteVisit →Visit →

What is MultiSpline?

MultiSpline went from five functions to a full multilevel spline framework in seven weeks.

MultiSpline fits spline-based nonlinear models to multilevel and longitudinal data in R. The package reached CRAN in February 2026 with five functions covering fitting, summary, prediction, plotting and intraclass correlations. Version 0.2.0, seven weeks later, adds cross-classified and nested random-effect structures, automatic knot selection, a multilevel R-squared variance partition, derivative-based interpretation with turning points, model comparison against polynomials, and cluster heterogeneity analysis, while keeping every 0.1.0 call valid.

Read the full MultiSpline trajectory →

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.

Read the full r2dii.analysis trajectory →

MultiSpline vs r2dii.analysis: editorial side-by-side

M
MultiSpline
ANALYTICS
0.0

MultiSpline went from five functions to a full multilevel spline framework in seven weeks.

◆ Current state

MultiSpline fits spline-based nonlinear models to multilevel and longitudinal data in R. The package reached CRAN in February 2026 with five functions covering fitting, summary, prediction, plotting and intraclass correlations. Version 0.2.0, seven weeks later, adds cross-classified and nested random-effect structures, automatic knot selection, a multilevel R-squared variance partition, derivative-based interpretation with turning points, model comparison against polynomials, and cluster heterogeneity analysis, while keeping every 0.1.0 call valid.

◆ Where it's heading

The arc is a research package being built out into a workflow at speed: 0.1.0 could fit a curve, 0.2.0 can tell you where the curve turns, how much variance each level explains, and whether a spline beats a polynomial at all. Backward compatibility was preserved across that expansion, which suggests the author is building for outside users rather than a single paper. The JOSS submission referenced in 0.1.1 points at academic distribution as the intended channel.

◆ Prediction

With the interpretation and diagnostics layers now in place, the next release will most likely extend the supported model families beyond the current lmer and glmer backends.

R0.0

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 MultiSpline 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 MultiSpline or r2dii.analysis.

See all MultiSpline alternatives → · See all r2dii.analysis alternatives →

Recent activity from MultiSpline and r2dii.analysis

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

  1. 4mo agoMultiSplineCross-classified and nested structures turn MultiSpline into a framework
  2. 5mo agoMultiSplineMultiSpline v0.1.1
  3. 5mo agoMultiSplineMultiSpline v0.1.0 - Initial Release
  4. 5mo agoMultiSplinev0.1.0.1
  5. 7mo agor2dii.analysisLow-carbon technology targets filled in for partial company coverage
  6. 1y agor2dii.analysisColumn definitions filled into the data dictionary
  7. 1y agor2dii.analysisPackage declared stable, three summarise functions soft-deprecated
  8. 2y agor2dii.analysisald argument removed for good in favour of abcd
  9. 2y agor2dii.analysisCompany-level SDA converges on the scenario's final year
  10. 3y agor2dii.analysisRepository moved to the RMI-PACTA organisation

Frequently asked questions

What is the difference between MultiSpline and r2dii.analysis?

Both compete on the same themes — r-package — within Analytics. MultiSpline 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 MultiSpline better than r2dii.analysis?

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

Top MultiSpline alternatives in Analytics are ranked by recent ship velocity. Browse the "MultiSpline alternatives" section above for the current picks, or visit /alternatives/multispline 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.