Citation

McLeod AI, Vingilis ER. Technometrics 2005; 47(2): 174-181.

Affiliation

Department of Statistical and Actuarial Sciences, University of Western Ontario, London, Ontario N6A 5B7, Canada, ( aimcleod@uwo.ca ).

Copyright

(Copyright © 2005)

DOI

10.1198/004017005000000094

PMID

19629193

PMCID

PMC2714195

Abstract

In many intervention analysis applications, time series data may be expensive or otherwise difficult to collect. In this case the power function is helpful, because it can be used to determine the probability that a proposed intervention analysis application will detect a meaningful change. Assuming that an underlying autoregressive integrated moving average (ARIMA) or fractional ARIMA model is known or can be estimated from the preintervention time series, the methodology for computing the required power function is developed for pulse, step, and ramp interventions with ARIMA and fractional ARIMA errors. Convenient formulas for computing the power function for important special cases are given. Illustrative applications in traffic safety and environmental impact assessment are discussed.

Language: en