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Comparison · Analytics
forecast vs mlr3mbo
A side-by-side editorial comparison of forecast and mlr3mbo — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-stats
forecast vs mlr3mbo: at a glance
What is forecast?
After years of pure maintenance, forecast 9.0.0 reopens the package
forecast is the long-established R forecasting package that fable was meant to succeed. For several years its releases were RNG fixes, base-R compatibility and documentation. Then 9.0.0 arrived with a batch of new model constructors, wider prediction-interval support and a rewritten accuracy() built on S3 methods.
What is mlr3mbo?
mlr3mbo picked its defaults from a benchmark study, not from taste
mlr3mbo does model-based and Bayesian optimisation for mlr3. Its 1.0.0 release added a dictionary of pre-built acquisition-function optimisers and, more consequentially, replaced the default surrogate, acquisition function and optimiser settings with values derived from a large-scale benchmark study. The releases since are corrections to the acquisition-optimiser path exposed by that new default configuration.
forecast vs mlr3mbo: editorial side-by-side
forecast
0.0ANALYTICS
After years of pure maintenance, forecast 9.0.0 reopens the package
◆ Current state
forecast is the long-established R forecasting package that fable was meant to succeed. For several years its releases were RNG fixes, base-R compatibility and documentation. Then 9.0.0 arrived with a batch of new model constructors, wider prediction-interval support and a rewritten accuracy() built on S3 methods.
◆ Where it's heading
The major version reframes forecast around explicit *_model() constructors — mean, random walk, spline, theta, Croston — rather than the older function-per-method style, and the 9.0.x patches since have been performance and argument-handling cleanups on top. That is an active maintenance line, not a package winding down in favour of fable.
◆ Prediction
Expect continued 9.0.x patches consolidating the new constructors and their forecast methods, with the older interfaces kept working alongside them.
mlr3mbo
2.5ANALYTICS
mlr3mbo picked its defaults from a benchmark study, not from taste
◆ Current state
mlr3mbo does model-based and Bayesian optimisation for mlr3. Its 1.0.0 release added a dictionary of pre-built acquisition-function optimisers and, more consequentially, replaced the default surrogate, acquisition function and optimiser settings with values derived from a large-scale benchmark study. The releases since are corrections to the acquisition-optimiser path exposed by that new default configuration.
◆ Where it's heading
The package has moved from a toolkit that expected users to assemble a Bayesian optimisation loop into one with a defensible default loop, and the recent fixes — warm-start sizing on multi-objective archives, silently discarded terminators, stale x_domain values — are the consequences of more people running the default path.
◆ Prediction
Expect continued hardening of the acquisition-optimiser classes rather than new acquisition functions.
Alternatives to forecast and mlr3mbo
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 forecast or mlr3mbo.
textrecipes
Text features finally stay sparse all the way to the model.
probably
The package that made calibration a step instead of an afterthought.
workflowsets
workflowsets keeps widening what counts as a model worth comparing.
workflows
The tidymodels pipeline grew a third stage, and it happens after the model runs.
vetiver
Posit's MLOps package went quiet for two years, then came back to keep up with recipes.
See all forecast alternatives → · See all mlr3mbo alternatives →
Recent activity from forecast and mlr3mbo
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 23d agomlr3mboAcquisition optimiser fixes for warm starts and archives
- 3mo agomlr3mboDictionary lookup and restart-limit fixes
- 4mo agomlr3mborush 1.0.0 compatibility and Surrogate$check()
- 4mo agoforecastFixes for checkresiduals() and mstl() lambda handling
- 5mo agomlr3mbomlr3mbo 1.0.0 ships benchmark-derived default settings ⚡
- 5mo agoforecastFaster ARFIMA search and forecast.mlm() argument handling
- 7mo agoforecastforecast 9.0.0 adds five model constructors and rewrites accuracy() ⚡
- 10mo agomlr3mbomlr3learners 0.13.0 compatibility
- 11mo agomlr3mboMaintainer change and mlr3pipelines 0.9.0 upkeep
- 1y agoforecastDocumentation and bug-fix release
- 2y agoforecastRNG state and base-R head/tail compatibility
- 2y agoforecastMuch faster hfitted() for ARIMA and ETS models
Frequently asked questions
What is the difference between forecast and mlr3mbo?
Both compete on the same themes — r-stats — within Analytics. mlr3mbo is currently shipping more aggressively (velocity 2.5 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.
Is forecast better than mlr3mbo?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. mlr3mbo is currently shipping more aggressively (velocity 2.5 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.
What are the best alternatives to forecast?
Top forecast alternatives in Analytics are ranked by recent ship velocity. Browse the "forecast alternatives" section above for the current picks, or visit /alternatives/forecast-r for the full list with editorial commentary on each.
What are the best alternatives to mlr3mbo?
Top mlr3mbo alternatives in Analytics are ranked by recent ship velocity. Browse the "mlr3mbo alternatives" section above for the current picks, or visit /alternatives/mlr3mbo for the full list with editorial commentary on each.