algo-forecast-exponential

Installation
SKILL.md

Exponential Smoothing

Overview

Exponential smoothing assigns exponentially decreasing weights to past observations. Three variants: Simple (SES, level only), Holt (level + trend), Holt-Winters (level + trend + seasonality). ETS framework (Error-Trend-Seasonality) provides a unified statistical model. Fast, interpretable, and competitive with complex models for short horizons.

When to Use

Trigger conditions:

  • Quick forecasting with minimal configuration
  • Short-horizon forecasts (1-2 seasonal cycles ahead)
  • Data with clear level, trend, and/or seasonal components

When NOT to use:

  • For long-range forecasts (uncertainty accumulates too fast)
  • When external regressors are important (use regression or ML models)

Algorithm

Related skills

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Installs
17
GitHub Stars
190
First Seen
Apr 10, 2026