ETS Tool

The ETS tool estimates a univariate time series forecasting model using an exponential smoothing method. Exponential smoothing is a commonly used forecasting approach that is based on a weighted average of past observations, with the weights declining in size for more distant past values (the weights are said to follow an exponential decay function). The tool is able to account for three time series components: level, trend, and seasonality. The tool can use fully automated methods to model the three components in the "best way" based on statistical criteria, or the user can specify the underlying methods used. An excellent discussion of the methods used can be found in Chapter 7 of Hyndman and Athanasopoulos's online book Forecasting: Principals and Practice*

This tool uses the R tool. Install R and the necessary packages by going to Options > Download Predictive Tools.

Input

An Alteryx data stream.

Configuration Properties

Required parameters

Model type

Other options

Graphics Options

Outputs

*Hyndman, R.J. and Athanasopoulos, G. (2012) Forecasting: Principles and Practice.