Introduction

The ESM procedure provides a quick way to generate forecasts for many time series or transactional data in one step by using exponential smoothing methods. All parameters associated with the forecasting model are optimized based on the data.

You can use the following smoothing models:

Additionally, PROC ESM can transform the data before applying the smoothing methods using any of these transformations:

In addition to forecasting, the ESM procedure can also produce graphic output.

The ESM procedure can forecast both time series data, whose observations are equally spaced at a specific time interval (for example, monthly, weekly), or transactional data, whose observations are not spaced with respect to any particular time interval. (Internet, inventory, sales, and similar data are typical examples of transactional data. For transactional data, the data are accumulated based on a specified time interval to form a time series.)