poissonreg
poissonreg gave its models away to parsnip and kept the glue — now it just keeps glmnet honest.
A side-by-side editorial comparison of fabletools and sass — release velocity, themes, recent moves, and the top alternatives to consider.
The tidyverts forecasting core rebuilt model combination on full residual covariance.
fabletools is the framework layer under fable and fpp3 — mables, fables, accuracy measures, reconciliation, and the model arithmetic that lets forecasters express ensembles as expressions. Version 0.8.0 reworked that arithmetic: combination now uses a joint N-way convolution accounting for the full residual covariance across components rather than composing pairwise, and every arithmetic operator collapses to a single model_combination with correctly implied weights, so nested expressions like ((m1 + m2)/2 + m3)/2 flatten automatically. In parallel, the package has been shedding graphics to {ggtime} on a deliberately slow deprecation clock.
Nine releases of compiler warnings and CRAN checks — the Sass binding is in pure upkeep.
sass compiles Sass to CSS for R, and its recent history is almost entirely about staying installable. The last ten releases are dominated by compilation warnings on new toolchains — Apple Clang 15, gcc-12, Windows — plus R CMD check fixes for r-devel and one LibSass version bump. The only user-visible changes in the set are the switch to woff2 font files in font_google(local = TRUE) and clearer output when Google fonts are downloaded.
fabletools is the framework layer under fable and fpp3 — mables, fables, accuracy measures, reconciliation, and the model arithmetic that lets forecasters express ensembles as expressions. Version 0.8.0 reworked that arithmetic: combination now uses a joint N-way convolution accounting for the full residual covariance across components rather than composing pairwise, and every arithmetic operator collapses to a single model_combination with correctly implied weights, so nested expressions like ((m1 + m2)/2 + m3)/2 flatten automatically. In parallel, the package has been shedding graphics to {ggtime} on a deliberately slow deprecation clock.
The framework is being narrowed and deepened at the same time. Narrowed, because plotting is moving out to a dedicated package over an announced two-year deprecation, leaving fabletools to modeling infrastructure. Deepened, because the recent statistical work targets correctness in places users could not easily inspect — combination weights, inverse-variance weighting computed on response rather than innovation residuals, reconciliation coherency matrices exposed via coherent_smat() and coherent_cmat(). Class hygiene follows the same instinct, with mdl_lst replacing lst_mdl and gaining augment(), glance(), and tidy() so global and reconciliation models report statistics like any other.
With combination and reconciliation infrastructure freshly reworked, the remaining announced work is the ggtime separation, so expect the graphics re-exports to keep degrading toward removal while modeling changes stay incremental.
sass compiles Sass to CSS for R, and its recent history is almost entirely about staying installable. The last ten releases are dominated by compilation warnings on new toolchains — Apple Clang 15, gcc-12, Windows — plus R CMD check fixes for r-devel and one LibSass version bump. The only user-visible changes in the set are the switch to woff2 font files in font_google(local = TRUE) and clearer output when Google fonts are downloaded.
This is a stable binding to a C++ library that is itself no longer moving, so the package's work is defined by the compilers and CRAN policies around it rather than by Sass features. Nothing in these entries suggests active development; the maintenance is competent and prompt, but it is maintenance.
The next release will most likely be triggered by a new compiler warning class or an R CMD check requirement rather than by anything in the Sass language. The entries give no signal of planned feature work.
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 fabletools or sass.
poissonreg gave its models away to parsnip and kept the glue — now it just keeps glmnet honest.
S7 has stopped adding surface and started proving it holds up against R itself.
R's torchvision is porting PyTorch's vision stack one task at a time — instance segmentation just landed.
The messy-date parser rewrote its core in Rust and came out 300x faster.
The legend engine mapsf spun out, now covering legend types the parent map package can draw.
R help pages translated on demand by whichever LLM you point it at.
See all fabletools alternatives → · See all sass alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-package — within Analytics. fabletools and sass 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. fabletools and sass 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.
Top fabletools alternatives in Analytics are ranked by recent ship velocity. Browse the "fabletools alternatives" section above for the current picks, or visit /alternatives/fabletools for the full list with editorial commentary on each.
Top sass alternatives in Analytics are ranked by recent ship velocity. Browse the "sass alternatives" section above for the current picks, or visit /alternatives/sass for the full list with editorial commentary on each.