Detecting changes in the ar parameters of a nonstationary arma process

George V. Moustakides · Albert Benveniste A

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Advanced Statistical Process Monitoring Control Systems and Identification Time Series Analysis and Forecasting

Abstract

We present a method for detecting changes in the AR parameters of an ARMA process with arbitrarily time varying MA parameters. Assuming that a collection of observations and a set of nominal time invariant AR parameters are given, we test if the observations are generated by the nominal AR parameters or by a different set of time invariant AR parameters. The detection method is derived by using a local asymptotic approach and it is based on an estimation procedure which was shown to be consistent under nonstationarities.

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1983Sequential detection of abrupt changes in spectral characteristics of digital signals

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1989Statistical analysis of “structural change”: An annotated bibliography 1994Quickest detection of an abrupt change in a random sequence with finite change-time

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