We propose new tests to detect a change in the mean of a time series. Like
many existing tests, the new ones are based on the CUSUM process. Existing
CUSUM tests require an estimator of a scale parameter to make them
asymptotically distribution free under the no change null hypothesis. Even if
the observations are independent, the estimation of the scale parameter is not
simple since the estimator for the scale parameter should be at least
consistent under the null as well as under the alternative. The situation is
much more complicated in case of dependent data, where the empirical spectral
density at 0 is used to scale the CUSUM process. To circumvent these
difficulties, new tests are proposed which are ratios of CUSUM functionals. We
demonstrate the applicability of our method to detect a change in the mean when
the errors are AR(1) and GARCH(1,1) sequences.Comment: Published in at http://dx.doi.org/10.1214/193940307000000220 the IMS
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