Stress-test time-series forecasters: known dynamical systems, controlled shocks, calibrated noise titration (the AURA protocol). Placeholder release; 0.1.0 in preparation.
Project description
serie
Stress-test your forecaster before reality does.
serie will implement the AURA protocol (Artificial Uncertainty and
Regime Alteration): take a clean reference series — a simulated dynamical
system with exact ground truth, or a clean recording treated as the
system — apply controlled non-stationary shocks, and inject calibrated
Gaussian observation noise at chosen levels. Measure exactly when and how
a forecaster breaks, instead of ranking models on one recorded history.
import serie
stock = serie.prepare("lorenz", seed=42)
for sigma in (0.0, 0.25, 1.0, 2.0):
split = serie.titrate(stock, sigma=sigma)
...
This is a 0.0.1 name reservation — the API above ships in 0.1.0. Watch github.com/QilinWang for the release.
MIT license. Author: Qilin Wang.
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