2.2.4.2 Single Exponential Smoothing

TSA-Smooth-SingleExp

Introduction

Single exponential smoothing is a technique used in time series analysis for smoothing data points based on the weighted average of past observations. It assigns exponentially decreasing weights to past observations, with more recent observations receiving higher weights. This method is particularly useful for data with no clear trend or seasonality.

Notes: To decide which smoothing tool is appropriate for your data, please refer to the summarized table in the page of Smooth.

More information:

• Tutorial: Single Exponential Smoothing
• Algorithm: Single Exponential Smoothing