Python Data Analysis Cookbook

Exponential smoothing

Exponential smoothing is a low-pass filter that aims to remove noise. In this recipe, we will apply single and double exponential smoothing, as shown by the following equations:

Single exponential smoothing (6.3) requires the smoothing factor α, where 0 < α < 1. Double exponential smoothing (6.4 and 6.5) attempts to handle trends in data via the trend smoothing factor β, where 0 < β < 1.

We will also take a look at rolling deviations of wind speed, which are similar to z-scores, but they are applied to a rolling window. Smoothing is associated with regression, although the goal of smoothing is to get rid of noise. Nevertheless, ...