Skill Claude CodeCodex
Backtesting, cross-validation, evaluation metrics, and conformal prediction intervals for the anofoxforecast DuckDB extension. Use when evaluating forecast accuracy, comparing models with time-series-aware CV, computing metrics (MAE / RMSE / MAPE / MASE / coverage), or attaching distribution-free prediction intervals…
Skill Claude CodeCodex
Data preparation for the anofoxforecast DuckDB extension — filling gaps, imputing nulls, dropping bad series, differencing, detrending, hierarchical key operations. Use when preparing raw time series for downstream forecasting or backtesting with tsforecastby / tscvfoldsby.
Skill Claude CodeCodex
Seasonality, changepoint, peak, and decomposition detection for the anofoxforecast DuckDB extension. Use when identifying seasonal periods before configuring seasonal forecasting models, detecting structural breaks, analysing peak timing regularity, or decomposing a series into trend / seasonal / residual components.
Skill Claude CodeCodex
Exploratory data analysis and data quality for the anofoxforecast DuckDB extension — 34 per-series statistics, data-quality scoring, quality-report summaries, and 117 tsfresh-compatible feature extraction. Use before forecasting to understand series characteristics (length, gaps, trend, seasonality strength…
Skill Claude CodeCodex
Forecasting models and the tsforecastby / tsforecastvarby API surface of the anofoxforecast DuckDB extension. Covers 36 models (baseline, exponential smoothing, state-space ARIMA + Kalman, classical GARCH, Theta, multi-seasonal, intermittent-demand, distributional Laplace with three variants, panel/global…
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