Simple Exponential Smoothing

Simple Exponential Smoothing (SES) is a forecasting method that uses the weighted average of past values to forecast for the present and future. It is a form of smoothing that weights each past observation exponentially. The weights get smaller as the values get older, so that recent values are given more weight. This allows the forecast to respond faster to recent data points and be more adaptive to trends in the data. At its most basic, it is just a weighted average of past values.