GACE: Generalized Adaptive Capped Estimator for Time Series
Forecasting
Provides deterministic forecasting for weekly, monthly, quarterly, and yearly
time series using the Generalized Adaptive Capped Estimator. The method
includes preprocessing for missing and extreme values, extraction of multiple
growth components (including long-term, short-term, rolling, and drift-based
signals), volatility-aware asymmetric capping, optional seasonal adjustment
via damped and normalized seasonal factors, and a recursive forecast
formulation with moderated growth. The package includes a user-facing
forecasting interface and a plotting helper for visualization. Related
forecasting background is discussed in Hyndman and Athanasopoulos (2021)
<https://otexts.com/fpp3/> and Hyndman and Khandakar (2008)
<doi:10.18637/jss.v027.i03>. The method extends classical extrapolative
forecasting approaches and is suited for operational and business planning
contexts where stability and interpretability are important.
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