An open library for your next question. Public pilot
Executable Science
Log inCreate account
← All resources
Software

StatsForecast

Statistical forecasting models and utilities for collections of time series.

Visit the original source ↗

External resource. No execution or independent verification is claimed here.

A QUESTION TO TAKE FURTHER

How do fixed classical forecasting methods compare on held-out synthetic seasonal regimes?

Generate and freeze all series, origins, horizons, metrics, and baselines before fitting; report every regime and avoid selecting favorable horizons.

What you could produce

  • A pinned, isolated reproducer with generated inputs and a concise result table
  • A separately controlled check report with fixed tolerances and disclosed limitations

Before you use it

  • A separately qualified runtime with the package and its reviewed, pinned dependency closure; no dependency installation is supported by the current self-contained Python pilot.

Limits to keep in view

  • No project source, package build hook, test, example, or submitted research command has been executed.
  • The documented pilot supports self-contained Python 3.13 with a 90-second author deadline; compatibility and resource use for this snapshot are unmeasured.

Source and permission context

Preserve the upstream project name, version, repository link, applicable notices, and contributor attribution when preparing an artifact for reuse.

Catalog listing reviewed. This review covers the description and source links displayed here.

Approved for catalog metadata and links. The displayed entry identifies StatsForecast with the concise collection-authored summary “Statistical forecasting models and utilities for collections of time series.” and points to the public upstream repository https://github.com/Nixtla/statsforecast. The wording describes function and possible investigation without reproducing upstream source or documentation, claiming execution, or implying endorsement or rights beyond the recorded scopes.

Reviewed 2026-09-14. Copying or adapting source files remains subject to their own terms.

code · Apache-2.0

Apache License version 2.0 identified in the fetched license file. Observation is limited to LICENSE at commit d31d8abfea69ec714074f5d6bbba131f5e9aec43; it is not a repository-wide rights clearance.

Inspect the license evidence ↗

Before copying source material

  • Bundled datasets, examples, submodules, vendored code, and dependency licenses have not been audited; the observed top-level license does not clear all of them.
  • README and documentation rights were not independently resolved from the main code license; this catalog only links and describes.