rjd3highfreq
rjd3highfreq ships whatever the Java side ships, and only occasionally says what that was.
Comparison · Analytics
broadcast vs modeltime.ensemble
A side-by-side editorial comparison of broadcast and modeltime.ensemble — release velocity, themes, recent moves, and the top alternatives to consider.
broadcast vs modeltime.ensemble: at a glance
What is broadcast?
broadcast is filling in NumPy-style array broadcasting for R, operator by operator.
broadcast brings dimension-broadcasting semantics to R arrays and lists — elementwise operations between arrays of mismatched shape, plus casting methods between hierarchical lists and dimensional structures. It reached CRAN in September 2025 and has released roughly monthly since, accumulating operators (nor, nand, longest common substring), casting methods (cast_shallow2atomic, cast_hier2dim, hiernames2dimnames), and helpers (vector2array, undim, mbroadcasters).
What is modeltime.ensemble?
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.
broadcast vs modeltime.ensemble: editorial side-by-side
broadcast
0.0ANALYTICS
broadcast is filling in NumPy-style array broadcasting for R, operator by operator.
◆ Current state
broadcast brings dimension-broadcasting semantics to R arrays and lists — elementwise operations between arrays of mismatched shape, plus casting methods between hierarchical lists and dimensional structures. It reached CRAN in September 2025 and has released roughly monthly since, accumulating operators (nor, nand, longest common substring), casting methods (cast_shallow2atomic, cast_hier2dim, hiernames2dimnames), and helpers (vector2array, undim, mbroadcasters).
◆ Where it's heading
The package is in its post-launch consolidation year, and the release notes read accordingly: roughly half of each entry is a consistency correction rather than an addition. Zero-length results now carry the right type, comparison operators accept integer and logical inputs, the comment attribute survives operations, and the nand operator was found to be wrongly defined against C++ short-circuit evaluation. That ratio is what a young package looks like while its edge cases are being found.
◆ Prediction
Expect more operators and casting methods on the same cadence, with continued type-consistency corrections as users exercise unusual input combinations. Nothing in the entries points at an architectural change.
modeltime.ensemble
0.0ANALYTICS
modeltime.ensemble wakes after four years, and the work is all tune 2.0 compatibility.
◆ Current state
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.
◆ Where it's heading
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.
◆ Prediction
Expect the next release to follow the next tune or modeltime.resample breaking change rather than to introduce new ensembling methods.
Alternatives to broadcast and modeltime.ensemble
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 broadcast or modeltime.ensemble.
audubon
audubon's release feed is almost entirely Renovate bumping the JavaScript toolchain behind its Japanese text splitter.
affiner
affiner is quietly turning a grid transformation helper into a small computational geometry library.
ageproR
ageproR spent two years chasing a moving file format, then added the recruitment models that justify the effort.
r-ledger
ledger adds a Rust toolchain fallback, so beancount imports work whether or not the Python tooling is installed.
gridpattern
gridpattern keeps widening its catalogue, and the newest patterns finally use the device's own line rendering.
See all broadcast alternatives → · See all modeltime.ensemble alternatives →
Recent activity from broadcast and modeltime.ensemble
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 2mo agobroadcastnor and longest-common-substring operators added; nand corrected
- 5mo agobroadcastcheckNULL, checkNA and ecumprob added
- 8mo agobroadcastZero-length results and attribute preservation made consistent
- 9mo agobroadcastacast dimnames bug fixed; casting and helper surface widens
- 10mo agobroadcastrecurse_classed replaced by recurse_all in casting methods
- 11mo agobroadcastTitle case fixed for CRAN submission
- 11mo agomodeltime.ensembleRealigned for tune 2.0.0 resampling changes
- 11mo agomodeltime.ensembleDrops the tidyverse dependency ahead of tune 2.0
- 5y agomodeltime.ensemblePer-series calibration IDs and parallel refitting
- 5y agomodeltime.ensembleRecursive ensembles for single and panel series ⚡
Frequently asked questions
What is the difference between broadcast and modeltime.ensemble?
They serve adjacent needs but don't currently overlap on shipped themes. broadcast and modeltime.ensemble 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.
Is broadcast better than modeltime.ensemble?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. broadcast and modeltime.ensemble 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.
What are the best alternatives to broadcast?
Top broadcast alternatives in Analytics are ranked by recent ship velocity. Browse the "broadcast alternatives" section above for the current picks, or visit /alternatives/broadcast-r for the full list with editorial commentary on each.
What are the best alternatives to modeltime.ensemble?
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.