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time-series-forecasting

Forecasting time-ordered data — ARIMA/state-space models, stationarity handling, backtesting, and honest prediction intervals.

skills/time-series-forecasting/SKILL.md

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## Overview

Forecasting turns time-ordered observations into decisions about the
future. This skill covers the classical forecasting toolkit
(decomposition, ARIMA/SARIMA, exponential smoothing, state-space
models), making series stationary, spectral analysis, and the
validation discipline — rolling-origin backtesting without leakage —
that separates real forecast skill from in-sample illusions.

## When to use

- Forecasting: demand, concentrations, prices, sensor readings, disease incidence
- Decomposing trend/seasonality/residuals for reporting or preprocessing
- Testing for unit roots, changepoints, or structural breaks