HydroPortailStats
France's national flood statistics, ported out of Fortran and into R.
A side-by-side editorial comparison of estimatr and simDAG — release velocity, themes, recent moves, and the top alternatives to consider.
Fast design-based estimators for experiments, coasting on CRAN patches.
estimatr provides the design-based regression estimators the DeclareDesign ecosystem is built on — robust and cluster-robust standard errors, blocked and clustered randomization inference — implemented for speed rather than generality. The last three releases carry no substantive notes: each is a merge commit for a CRAN patch, one of them accompanied by a typo fix.
simDAG grew a second simulation engine, then spent two releases surviving upstream breakage.
simDAG generates data from directed acyclic graphs, with a library of node types covering Gaussian, binomial, Poisson, negative binomial, zero-inflated, ordered regression, Cox, and Aalen models. The 1.0.0 milestone opened node_cox() to arbitrary baseline hazard functions, which lets continuous time-dependent hazards drive discrete-event simulations. The two most recent releases exist only to keep the package on CRAN through breakage in lme4 and simr.
estimatr provides the design-based regression estimators the DeclareDesign ecosystem is built on — robust and cluster-robust standard errors, blocked and clustered randomization inference — implemented for speed rather than generality. The last three releases carry no substantive notes: each is a merge commit for a CRAN patch, one of them accompanied by a typo fix.
Direction cannot be read from this feed. The release notes are unedited merge-commit messages, so the only signal is cadence — roughly annual, each release framed as a CRAN patch rather than as feature work. That pattern is consistent with a package whose estimators are considered finished and which now moves only when CRAN policy requires it.
On the evidence here the next release is another CRAN compliance patch, but the notes are too thin to support a confident read of what the maintainers are actually working on.
simDAG generates data from directed acyclic graphs, with a library of node types covering Gaussian, binomial, Poisson, negative binomial, zero-inflated, ordered regression, Cox, and Aalen models. The 1.0.0 milestone opened node_cox() to arbitrary baseline hazard functions, which lets continuous time-dependent hazards drive discrete-event simulations. The two most recent releases exist only to keep the package on CRAN through breakage in lme4 and simr.
The package has been widening what a simulation can represent rather than deepening any one node. Networks arrived in 0.4.0 so individuals could depend on each other, discrete-event simulation in continuous time arrived in 0.5.0 as an alternative to the discrete-time engine, and 1.0.0 connected the two by letting continuous hazards feed the event-driven path. Alongside that, node types keep accumulating for outcome families the framework could not previously generate.
Expect the node library to keep expanding into outcome types the discrete-event engine can now support, though the recent releases suggest upstream dependency churn will keep consuming release slots.
Other Infra & APIs 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 estimatr or simDAG.
France's national flood statistics, ported out of Fortran and into R.
Sign, zero and narrative restrictions brought into the bsvars ecosystem.
The grammar of uncertainty visualization, now drawing the uncertainty in its own estimates.
IP address vectors for R that hit 1.0 and then went quiet.
A column-key toolkit for stitching decades of ecological field data into one table.
Microsoft's automated forecasting framework, still mostly a one-maintainer effort.
See all estimatr alternatives → · See all simDAG alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — causal-inference, r-package — within Infra & APIs. simDAG 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.
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. simDAG 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 Infra & APIs products to evaluate alongside.
Top estimatr alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "estimatr alternatives" section above for the current picks, or visit /alternatives/estimatr for the full list with editorial commentary on each.
Top simDAG alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "simDAG alternatives" section above for the current picks, or visit /alternatives/simdag for the full list with editorial commentary on each.