Abstract
In this paper, we propose two ratio-type statistics to sequentially detect the memory parameter change-points in the long-memory time series. The limiting distributions of monitoring statistics under the no-change-point null hypothesis as well as their consistency under the alternative hypothesis are proved. In particular, a sieve bootstrap approximation method is proposed to determine the critical values. Extensive simulations indicate that the new monitoring procedures perform well in finite samples. Finally, we illustrate our monitoring procedures by two sets of real data.
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