NonlinearSSM._prepare#

NonlinearSSM._prepare(y)[source]#

Coerce data to (n, p), promoting a 1-D series when p is one.

Raises:

DimensionError – If the data cannot match the observation dimension.
SpecificationError – If a row is partially observed – this engine treats missingness whole-row, and silently discarding the observed elements would misstate the likelihood.

Return type:

NDArray[double]

API reference

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

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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 · updated 2026-10-13 · built with Sphinx 9.1.0 and the PyData Sphinx Theme