Forecasting Process Details |

Intervention Effects |

Interventions are used for modeling events that occur at specific times. That is, they are known changes that affect the dependent series or outliers.

The *i*th intervention series is included in the output data set with variable name _INTV*i* _, which is a reserved variable name.

The point intervention is a one-time event. The *i*th intervention series has a point intervention at time when the series is nonzero only at time —that is,

Step interventions are continuing, and the input time series flags periods after the intervention. For a step intervention, before time , the *i*th intervention series is zero and then steps to a constant level thereafter—that is,

A ramp intervention is a continuing intervention that increases linearly after the intervention time. For a ramp intervention, before time , the *i*th intervention series is zero and increases linearly thereafter—that is, proportional to time.

Given the *i*th intervention series , you can define how the intervention takes effect by filters (transfer functions) of the form

where is the backshift operator .

The denominator of the transfer function determines the decay pattern of the intervention effect, whereas the numerator terms determine the size of the intervention effect time window.

For example, the following intervention effects are associated with the respective transfer functions.

- Immediately
- Gradually
- 1 lag window
- 3 lag window

The notation used to describe intervention effects has the form *type* :*t* (*q*)/(*p*), where *type* is point, step, or ramp; *t* is the time of the intervention (for example, OCT87); *q* is the transfer function numerator order; and *p* is the transfer function denominator order. If , the part "(*q*)" is omitted; if , the part "/(*p*)" is omitted.

In the Intervention Specification window, the `Number of Lags` option specifies the transfer function numerator order *q*, and the `Effect Decay Pattern` option specifies the transfer function denominator order *p*. In the `Effect Decay Pattern options`, values and resulting *p* are: `None`, ; `Exp`, ; `Wave`, .

For example, a step intervention with date 08MAR90 and effect pattern `Exp` is denoted "Step:08MAR90/(1)" and has a transfer function filter . A ramp intervention immediately applied on 08MAR90 is denoted "Ramp:08MAR90" and has a transfer function filter .

Copyright © 2008 by SAS Institute Inc., Cary, NC, USA. All rights reserved.