RMVMR
RMVMR is being tidied in lockstep with MVMR, the package it wraps
A side-by-side editorial comparison of cfrnow and modeltime.ensemble — release velocity, themes, recent moves, and the top alternatives to consider.
A Bayesian real-time CFR estimator that now ships stratified fits and posterior-predictive checks
cfrnow estimates case fatality ratios from line-list data while an outbreak is still running, using a Bayesian mixture-cure survival model registered as an `epidist` model type. Three releases in a month took it from first public release to stratified, partially-pooled fits with posterior-predictive checking. It leans on `distspec` for delay parameterisation, which reached CRAN alongside the 0.2.1 patch.
modeltime.ensemble wakes after four years, and the work is all tune 2.0 compatibility.
modeltime.ensemble builds average, weighted and stacked ensembles over modeltime forecast models. After a four-year gap it shipped twice in a fortnight during August and September 2025, both releases devoted to tracking breaking changes in tidymodels' tune package — new resampling column conventions, key uniqueness across resamples, recipe preparation. The tidyverse dependency was dropped in the same pass.
cfrnow estimates case fatality ratios from line-list data while an outbreak is still running, using a Bayesian mixture-cure survival model registered as an `epidist` model type. Three releases in a month took it from first public release to stratified, partially-pooled fits with posterior-predictive checking. It leans on `distspec` for delay parameterisation, which reached CRAN alongside the 0.2.1 patch.
The arc runs from producing a single corrected CFR number toward supporting a full model-checking workflow. 0.2.0 added the pieces a modeller needs to defend an estimate: replicate line lists replayed through the real-time truncation, an ascertainment-ratio correction for when fatal and non-fatal cases enter the line list at different rates, and per-group CFRs from `brms` formulas. Delay coverage widened from LogNormal and Gamma to Weibull in the same release.
Expect the next release to keep widening covariate and pooling support rather than adding new outcome types, since every 0.2.0 addition extended the existing formula interface instead of replacing it.
modeltime.ensemble builds average, weighted and stacked ensembles over modeltime forecast models. After a four-year gap it shipped twice in a fortnight during August and September 2025, both releases devoted to tracking breaking changes in tidymodels' tune package — new resampling column conventions, key uniqueness across resamples, recipe preparation. The tidyverse dependency was dropped in the same pass.
This is a package whose forecasting capability was settled by 2021 — recursive ensembles, per-series calibration — and whose recent life is dictated entirely by upstream tidymodels churn. New contributors did that compatibility work, including one from the tidymodels side. It now requires tune 2.0.0 and modeltime.resample 0.3.0, pinning it to the current tidymodels generation rather than straddling versions.
Expect the next release to follow the next tune or modeltime.resample breaking change rather than to introduce new ensembling methods.
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 cfrnow or modeltime.ensemble.
RMVMR is being tidied in lockstep with MVMR, the package it wraps
geoarrow tracks the GeoArrow spec and otherwise just keeps compiling
n2khab keeps retracting interpretations of habitat data it can't actually support
tidypolars is grinding toward complete dplyr coverage, one supported function at a time
OneSampleMR found that argument order in a formula was silently changing its estimates
bpbounds found the same swapped-cell bug twice and clamped its bounds back into range
See all cfrnow alternatives → · See all modeltime.ensemble alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. cfrnow is currently shipping more aggressively (velocity 5.0 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. cfrnow is currently shipping more aggressively (velocity 5.0 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.
Top cfrnow alternatives in Analytics are ranked by recent ship velocity. Browse the "cfrnow alternatives" section above for the current picks, or visit /alternatives/cfrnow for the full list with editorial commentary on each.
Top modeltime.ensemble alternatives in Analytics are ranked by recent ship velocity. Browse the "modeltime.ensemble alternatives" section above for the current picks, or visit /alternatives/modeltime-ensemble for the full list with editorial commentary on each.