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anofox-forecast-detectionlisted

Seasonality, changepoint, peak, and decomposition detection for the anofox_forecast 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.
DataZooDE/anofox-forecast · ★ 35 · AI & Automation · score 74
Install: claude install-skill DataZooDE/anofox-forecast
# Anofox Forecast — Detection & Decomposition Cheat Sheet **Extension:** `anofox_forecast` v0.15.3 | **DuckDB:** v1.4.5 LTS / v1.5.4+ | **Dual naming:** `ts_*` and `anofox_fcst_ts_*` Detect signal structure — **seasonality is not auto-detected by the forecasters**; you must run detection first and pass `seasonal_period` explicitly to `ts_forecast_by`. ## Requires: json extension Detection functions use the `json` extension for parameter marshalling. Enable auto-load once per session: ```sql SET autoinstall_known_extensions = 1; SET autoload_known_extensions = 1; ``` ## Period detection — 12 methods ### `ts_detect_periods_by` — primary entry point ```sql ts_detect_periods_by(source VARCHAR, group_col COLUMN, date_col COLUMN, value_col COLUMN, params MAP/STRUCT) → TABLE ``` Output columns (group column name is preserved): | Column | Type | Description | |---|---|---| | `<group_col>` | (input type) | Preserved group column (e.g. `product_id`) | | `periods` | `STRUCT(period, confidence, strength, amplitude, phase, iteration, ...)[]` | Array of detected periods | | `n_periods` | BIGINT | Count of detected periods | | `primary_period` | DOUBLE | Top-level primary period (convenience, avoids struct indexing) | | `method` | VARCHAR | Method that produced the result | Params: | Key | Default | Description | |---|---|---| | `method` | `'fft'` | Detection method (see table below) | | `max_period` | series length / 2 | Upper bound on detected period | | `