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@dennisbader, the workflow is waiting for maintainer approval. Could you approve the run when you have a chance? I'd also appreciate your view on the AirPassengers benchmark adjustment discussed in #3286. The PR keeps the formula correction separate from any new detrending logic, and the existing benchmark accuracy limits are unchanged. Happy to adjust the scope based on your feedback. |
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Checklist before merging this PR:
Fixes #3286.
Summary
check_seasonality()scales Bartlett's standard error by the empirical mean and variance of the ACF. For white noise, that multiplier can be close to zero or negative, making insignificant peaks look seasonal.This uses the normal critical value directly and passes the actual lag to
_bartlett_formula(), so its sum includes all preceding nonzero-lag autocorrelations. Public signatures, candidate selection and return conventions are unchanged.Regression tests cover seeded white noise, Bartlett confidence intervals from statsmodels at three significance levels, noisy periods 2/6/12, and default Theta/FourTheta fitting and forecasting.
The corrected test also changes automatic detection on the trending AirPassengers benchmark: its lag-12 ACF is below the corrected cutoff. Those forecasting fixtures now specify the known annual period explicitly, keeping their existing accuracy limits. Default automatic detection is tested separately. The changelog notes that inferred periods and forecasts can change; there is no new detrending or multiple-testing correction.
Thanks @akshpatel0910 for the detailed reproduction.
Other Information
darts/tests/utils,test_4theta.pyandtest_local_forecasting_models.py. Skips are optional-dependency cases; no test-selection exclusions were used.These are CPU/core-dependency test runs, not the full optional-model CI matrix.