Overview
Exponential smoothing is a popular forecasting method that applies decreasing weights to older observations. Unlike simple moving averages, it doesn't require a large amount of historical data to be stored.
Variations
- Simple Exponential Smoothing: For data with no trend or seasonality.
- Holt's Linear Smoothing: For data with a trend but no seasonality.
- Holt-Winters Smoothing: For data with both trend and seasonality.
Key Parameter
Alpha (α): The smoothing constant (between 0 and 1). A higher alpha gives more weight to recent data.