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Locally Optimal Properties of the Durbin-Watson Test

Published online by Cambridge University Press:  18 October 2010

Maxwell L. King
Affiliation:
Monash University, Australia
Merran A. Evans
Affiliation:
Monash University, Australia

Abstract

Although originally designed to detect AR(1) disturbances in the linear-regression model, the Durbin-Watson test is known to have good power against other forms of disturbance behavior. In this paper, we identify disturbance processes involving any number of parameters against which the Durbin–Watson test is approximately locally best invariant uniformly in a range of directions from the null hypothesis. Examples include the sum of q independent ARMA(1,1) processes, certain spatial autocorrelation processes involving up to four parameters, and a stochastic cycle model.

Type
Brief Report
Copyright
Copyright © Cambridge University Press 1988 

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