HydroPortailStats
France's national flood statistics, ported out of Fortran and into R.
A side-by-side editorial comparison of bolasso and estimatr — release velocity, themes, recent moves, and the top alternatives to consider.
Bootstrap lasso got a fast mode, a second selection rule, and multinomial support
bolasso implements the bootstrapped lasso, refitting a regularized regression across bootstrap replicates and selecting variables by how consistently they survive. The 0.3.0 release reshaped it: a fast argument computes one cross-validated lambda on the full dataset instead of cross-validating inside every replicate, and selected_variables() gained a choice between the variable inclusion probability rule and a quantile rule based on bootstrap confidence intervals. Since then 0.4.0 exposed the bootstrap indices through bootstrap_samples(), and 0.5.0 extended the whole surface to multinomial responses, returning one list element per outcome level.
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.
bolasso implements the bootstrapped lasso, refitting a regularized regression across bootstrap replicates and selecting variables by how consistently they survive. The 0.3.0 release reshaped it: a fast argument computes one cross-validated lambda on the full dataset instead of cross-validating inside every replicate, and selected_variables() gained a choice between the variable inclusion probability rule and a quantile rule based on bootstrap confidence intervals. Since then 0.4.0 exposed the bootstrap indices through bootstrap_samples(), and 0.5.0 extended the whole surface to multinomial responses, returning one list element per outcome level.
The package spent 2022 dormant after its initial releases and has been actively developed since late 2024, moving from a single algorithm toward a workbench. The additions cluster around inspection rather than estimation: tidy() for bootstrap-level coefficients, plot_selection_thresholds() for selection stability across thresholds, plot_selected_variables() for the surviving covariates, and now the extracted bootstrap indices. Documented gaps remain, with mgaussian unsupported and multinomial prediction limited to class output.
The two stated limitations in 0.5.0 - no mgaussian family and class-only multinomial prediction - are the most likely next targets, since the maintainer flagged both as possible later additions.
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.
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 bolasso or estimatr.
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 bolasso alternatives → · See all estimatr alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-package — within Infra & APIs. bolasso and estimatr 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.
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. bolasso and estimatr 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 Infra & APIs products to evaluate alongside.
Top bolasso alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "bolasso alternatives" section above for the current picks, or visit /alternatives/bolasso for the full list with editorial commentary on each.
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.