compositional.mle
An MLE package rebuilt around composable solvers, then renamed to match.
Comparison · Analytics
DHARMa vs topocast
A side-by-side editorial comparison of DHARMa and topocast — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-package
DHARMa vs topocast: 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 topocast?
New R package downscaling coarse climate rasters onto fine terrain, now five times cheaper per call.
topocast is a young R package — first released in June 2026 — that downscales coarse rasters onto fine terrain using moving-window regression, with the relationship expressed as a formula over layer names. Its defining implementation choice is summed-area tables, which make the cost of estimating coefficient grids independent of the window radius. Three releases in six weeks have taken it from first publication through real-workflow fixes to a substantial performance restructuring.
DHARMa vs topocast: 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.
topocast
2.5ANALYTICS
New R package downscaling coarse climate rasters onto fine terrain, now five times cheaper per call.
◆ Current state
topocast is a young R package — first released in June 2026 — that downscales coarse rasters onto fine terrain using moving-window regression, with the relationship expressed as a formula over layer names. Its defining implementation choice is summed-area tables, which make the cost of estimating coefficient grids independent of the window radius. Three releases in six weeks have taken it from first publication through real-workflow fixes to a substantial performance restructuring.
◆ Where it's heading
Development is being driven by running the package against real datasets — the second release names CHELSA and SRTM as the source of its three fixes — and the third is a direct response to multi-response calls repeating work. The arc is the ordinary one for a new method package: publish the method, then discover that real inputs have more responses, more coordinate-system edge cases, and more repeated structure than the initial design assumed. Coefficient grids being exposed as output suggests the local regression parameters, such as lapse rate, are as interesting to users as the downscaled values.
◆ Prediction
Expect continued work on multi-response and time-series throughput, and more coordinate-system and input-validation handling as the package meets further real climate datasets.
Alternatives to DHARMa and topocast
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 topocast.
nabla
nabla dropped its C++ engine to chase exact derivatives at any order.
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.
See all DHARMa alternatives → · See all topocast alternatives →
Recent activity from DHARMa and topocast
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 26d agotopocastMulti-response calls stop repeating the coarse-to-target trip
- 2mo agotopocastCoefficient grids exposed and coarse predictors derived automatically
- 2mo agotopocastFirst release: terrain downscaling by moving-window regression
- 2mo agoDHARMaConditional simulation becomes the GLMM default, changing residuals ⚡
- 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 topocast?
Both compete on the same themes — r-package — within Analytics. topocast is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.
Is DHARMa better than topocast?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. topocast is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. 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 topocast?
Top topocast alternatives in Analytics are ranked by recent ship velocity. Browse the "topocast alternatives" section above for the current picks, or visit /alternatives/topocast for the full list with editorial commentary on each.