osmapiR
osmapiR is the rare API client that tracks its server's wiki revision numbers in the changelog.
A side-by-side editorial comparison of fabletools and sdtm.oak — 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.
Two releases in, the open-source SDTM toolkit now covers the domains it originally excluded.
sdtm.oak builds SDTM datasets — the tabulation standard clinical trial submissions are filed in — from raw collected data. The 0.1.0 release shipped the mapping algorithm functions and derived-variable helpers but explicitly excluded DM, trial design domains, and several others. Version 0.2.0 closes the largest of those gaps, adding DM domain support via calc_min_max_date() and oak_calc_ref_dates(), plus generate_sdtm_supp() for supplemental qualifier domains.
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.
sdtm.oak builds SDTM datasets — the tabulation standard clinical trial submissions are filed in — from raw collected data. The 0.1.0 release shipped the mapping algorithm functions and derived-variable helpers but explicitly excluded DM, trial design domains, and several others. Version 0.2.0 closes the largest of those gaps, adding DM domain support via calc_min_max_date() and oak_calc_ref_dates(), plus generate_sdtm_supp() for supplemental qualifier domains.
This is the pharmaverse pattern of building submission tooling in the open, one domain class at a time, with the release history running through GitHub release-candidate tags before each CRAN submission. The direction is clear from the domain checklist: start with the mechanically simple Findings and Events domains, then work toward the ones with cross-dataset dependencies. DM and SUPP were the two that most often forced teams back to bespoke code.
The remaining exclusions from the 0.1.0 scope — trial design domains, SV, SE, RELREC and the EPOCH variable — are the obvious next targets, with EPOCH likely first since it depends on the reference dates 0.2.0 just added. Expect the same rhythm of release candidates ahead of each CRAN submission.
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 sdtm.oak.
osmapiR is the rare API client that tracks its server's wiki revision numbers in the changelog.
ymlthis retired itself, naming Quarto as the reason it no longer needs to exist.
forestly built an interactive safety review tool, then taught it to produce submission-ready RTF.
pharmaverseadam is the pharmaverse's test-data mirror, and it now covers neurology.
pkglite's whole job is knowing which files in an R package are text — and it keeps getting better at guessing.
gMCPLite exists to be gMCP without Java, and its releases guard that boundary rather than extend it.
See all fabletools alternatives → · See all sdtm.oak alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-package — within Analytics. fabletools and sdtm.oak 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 sdtm.oak 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 sdtm.oak alternatives in Analytics are ranked by recent ship velocity. Browse the "sdtm.oak alternatives" section above for the current picks, or visit /alternatives/sdtm-oak for the full list with editorial commentary on each.