ConditionalForecastResult.unconditional#

ConditionalForecastResult.unconditional: NDArray[float64]#

(steps, k) mean path with no conditions imposed, \(\mu_h\).

The result’s own point forecast for a point result; the mean of the per-draw point forecasts for a sampled one. Kept out of the repr.

API reference

Every public model, test and result, with the mathematics it implements and a runnable example.

View the API

Examples

Research workflows on live FRED data, from identification to forecast evaluation, as scripts and notebooks.

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Engine

The numerical core and internal layers the public surface is built on, for contributors and the curious.

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Get cultivars

Pre-releases are published to PyPI and announced on GitHub Releases. Pin the exact version in anything that must not move.

pip install --pre cultivars==1.0.0a4

© 2026, Nikhil Sunder. Released under the MIT License. cultivars is an independent open-source project and is not affiliated with the Federal Reserve Bank of St. Louis; FRED® is a registered trademark of the Federal Reserve Bank of St. Louis.

cultivars 1.0.0a4 · built with Sphinx 9.1.0 and the PyData Sphinx Theme