#
The ESM Procedure

The ESM procedure generates forecasts by using exponential smoothing models with optimized
smoothing weights for many time series or transactional data.
The procedure can forecast both time series data, whose observations are equally spaced by a
specific time interval (for example, monthly or 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 prior to modeling and forecasting.

The following are highlights of the ESM procedure's capabilities:

- provides the following smoothing models:
- simple
- double
- linear
- damped trend
- seasonal
- Winters method (additive and multiplicative)

- provides the following transformions prior to modeling:
- log
- square root
- logistic
- Box-Cox

- supports ODS Graphics
- writes the time series extrapolated by the forecasts, the series summary statistics,
the forecasts and confidence limits, the parameter estimates, and the fit statistics
to output data sets.

## Documentation

For further details, see the *SAS/ETS*^{®} User's Guide

## Examples