Process or Product Monitoring and Control
6.4. Introduction to Time Series Analysis
6.4.3. What is Exponential Smoothing?
|Example comparing single, double, triple exponential smoothing||
This example shows comparison of single, double and triple exponential
smoothing for a data set.
The following data set represents 24 observations. These are six years of quarterly data (each year = 4 quarters).
|Table showing the data for the example||
|Plot of raw data with single, double, and triple exponential forecasts|
|Plot of raw data with triple exponential forecasts||
|Comparison of MSE's||
The updating coefficients were chosen by a computer program such that the MSE for each of the methods was minimized.
|Example of the computation of the Initial Trend|
|Computation of initial trend||
The data set consists of quarterly sales data. The season is
1 year and since there are 4 quarters per year, L = 4.
Using the formula we obtain:
|Example of the computation of the Initial Seasonal Indices|
|Table of initial seasonal indices||
In this example we used the full 6 years of data. Other schemes may use only 3, or some other number of years. There are also a number of ways to compute initial estimates.