论文信息 - Detecting changes in the ar parameters of a nonstationary arma process

Detecting changes in the ar parameters of a nonstationary arma process

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.

A. Benveniste | G. Moustakides

[1] William Feller,et al. An Introduction to Probability Theory and Its Applications , 1967 .

[2] George G. Roussas,et al. Contiguity of probability measures: some applications in statistics: Preface , 1972 .

[3] K. Åström,et al. Uniqueness of the maximum likelihood estimates of the parameters of an ARMA model , 1974 .

[4] Alan S. Willsky,et al. A survey of design methods for failure detection in dynamic systems , 1976, Autom..

[5] P. Hall,et al. Martingale Limit Theory and Its Application , 1980 .

[6] T. Söderström,et al. Optimal instrumental variable estimation and approximate implementations , 1983 .

[7] Michèle Basseville,et al. Sequential detection of abrupt changes in spectral characteristics of digital signals , 1983, IEEE Trans. Inf. Theory.

[8] A. Benveniste,et al. Single sample modal identification of a nonstationary stochastic process , 1985, IEEE Transactions on Automatic Control.

[9] George V. Moustakides,et al. Detection and diagnosis of abrupt changes in modal characteristics of nonstationary digital signals , 1986, IEEE Trans. Inf. Theory.