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Comparison · Analytics
forecast vs loo
A side-by-side editorial comparison of forecast and loo — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-stats
forecast vs loo: 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 loo?
loo keeps rewriting the diagnostics Bayesian modellers read off model comparison
loo computes leave-one-out cross-validation and model comparison for Bayesian models in the Stan ecosystem. Two releases in this window changed what users actually read: 2.7.0 replaced the fixed Pareto-k thresholds with sample-size-dependent ones and dropped the middle category, and 2.10.0 reshaped loo_compare's output into a data.frame with new uncertainty columns. The releases between are diagnostic robustness fixes and moment-matching corrections.
forecast vs loo: 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.
loo
2.5ANALYTICS
loo keeps rewriting the diagnostics Bayesian modellers read off model comparison
◆ Current state
loo computes leave-one-out cross-validation and model comparison for Bayesian models in the Stan ecosystem. Two releases in this window changed what users actually read: 2.7.0 replaced the fixed Pareto-k thresholds with sample-size-dependent ones and dropped the middle category, and 2.10.0 reshaped loo_compare's output into a data.frame with new uncertainty columns. The releases between are diagnostic robustness fixes and moment-matching corrections.
◆ Where it's heading
The package is being brought in line with the current PSIS literature rather than extended with new features, and the practical effect is that the numbers practitioners quote in papers keep changing meaning. Work is increasingly delegated to posterior for shared computations, and the project has added contributor process, benchmarks and a published AI contribution policy.
◆ Prediction
Expect further work on comparison diagnostics — the p_worse and diag_* columns are new enough that their defaults and documentation will likely be revised next.
Alternatives to forecast and loo
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 loo.
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 loo alternatives →
Recent activity from forecast and loo
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 20d agoloopsis_smooth_tail revert and simplify arg restored
- 1mo agolooloo_compare returns a data.frame with new uncertainty columns ⚡
- 4mo agoforecastFixes for checkresiduals() and mstl() lambda handling
- 5mo agoforecastFaster ARFIMA search and forecast.mlm() argument handling
- 7mo agoforecastforecast 9.0.0 adds five model constructors and rewrites accuracy() ⚡
- 7mo agolooStacking overflow fixes and posterior-based ESS
- 1y agoforecastDocumentation and bug-fix release
- 2y agolooMore robust Pareto-k diagnostics and moment matching
- 2y agoforecastRNG state and base-R head/tail compatibility
- 2y agoforecastMuch faster hfitted() for ARIMA and ETS models
- 2y agolooPareto-k thresholds now depend on sample size ⚡
- 3y agolooLOO predictive metrics and CRPS scoring functions
Frequently asked questions
What is the difference between forecast and loo?
Both compete on the same themes — r-stats — within Analytics. loo 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 loo?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. loo 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 loo?
Top loo alternatives in Analytics are ranked by recent ship velocity. Browse the "loo alternatives" section above for the current picks, or visit /alternatives/loo for the full list with editorial commentary on each.