compositional.mle
An MLE package rebuilt around composable solvers, then renamed to match.
Comparison · Analytics
DHARMa vs nabla
A side-by-side editorial comparison of DHARMa and nabla — release velocity, themes, recent moves, and the top alternatives to consider.
DHARMa vs nabla: 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 nabla?
nabla dropped its C++ engine to chase exact derivatives at any order.
nabla does forward-mode automatic differentiation in R using dual numbers, returning derivatives exact to machine precision rather than approximated by finite differences. It shipped as dualr in January 2026, then a day later released 0.5.0 under a changed identity: derivatives generalise from a hardcoded second order to arbitrary order through recursive nesting, and the Rcpp and C++ fast paths are deleted so the package is pure R. The current release, 0.7.1, is CRAN resubmission cleanup.
DHARMa vs nabla: 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.
nabla
0.0ANALYTICS
nabla dropped its C++ engine to chase exact derivatives at any order.
◆ Current state
nabla does forward-mode automatic differentiation in R using dual numbers, returning derivatives exact to machine precision rather than approximated by finite differences. It shipped as dualr in January 2026, then a day later released 0.5.0 under a changed identity: derivatives generalise from a hardcoded second order to arbitrary order through recursive nesting, and the Rcpp and C++ fast paths are deleted so the package is pure R. The current release, 0.7.1, is CRAN resubmission cleanup.
◆ Where it's heading
The 0.5.0 release note states the positioning explicitly: exact machine-precision derivatives at any order, not speed. Removing compiled code to make that claim coherent is an unusual direction, most numerical R packages move the other way, and it commits the package to a niche where correctness beats throughput. The old second-order API survives as deprecated thin wrappers, so the pivot was made without stranding early users. The rapid rename and version jump suggest identity was settled late.
◆ Prediction
Expect CRAN acceptance to be followed by work on the optimiser and MLE integration paths, where arbitrary-order derivatives have the clearest use.
Alternatives to DHARMa and nabla
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 nabla.
snowflakeauth
Eight months from first release to keyring caching and workload identity.
kwb.geosalz
A research-project workflow package where the interesting work is in the plumbing.
cyclocomp
A cyclomatic complexity checker that ships once every couple of years, and lands when it does.
revdbayes
Extreme value sampling in pure upkeep mode, mostly answering to Rcpp and CRAN.
lazyeval
A package retired in 2017 just got rewritten against R's public C API.
See all DHARMa alternatives → · See all nabla alternatives →
Recent activity from DHARMa and nabla
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 2mo agoDHARMaConditional simulation becomes the GLMM default, changing residuals ⚡
- 5mo agonablaCRAN resubmission cleanup after reviewer feedback
- 6mo agonablaArbitrary-order exact derivatives arrive; compiled code removed ⚡
- 6mo agonablaFirst release as dualr: dual-number autodiff with MLE helpers
- 1y agoDHARMaDHARMa 0.4.7
- 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 nabla?
They serve adjacent needs but don't currently overlap on shipped themes. DHARMa and nabla 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 nabla?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. DHARMa and nabla 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 nabla?
Top nabla alternatives in Analytics are ranked by recent ship velocity. Browse the "nabla alternatives" section above for the current picks, or visit /alternatives/nabla for the full list with editorial commentary on each.