Detecting changes in the ar parameters of a nonstationary arma process

DOI10.1080/17442508608833370zbMath0598.62105OpenAlexW2025329117MaRDI QIDQ3732797

Albert Benveniste, George V. Moustakides

Publication date: 1986

Published in: Stochastics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/17442508608833370

zbMATH Keywords

asymptotic distributionasymptotic normalitychange pointinstrumental variables methoddetection of parameter changenon-stationary ARMA process

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Non-Markovian processes: hypothesis testing (62M07)

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Subspace-based fault detection robust to changes in the noise covariances ⋮ Subspace-based algorithms for structural identification, damage detection, and sensor data fusion ⋮ Detecting changes in signals and systems - a survey ⋮ Autoregressive and adaptive estimation with an application to hurricane track prediction ⋮ Subspace-based fault detection algorithms for vibration monitoring ⋮ Detection and diagnosis of changes in the eigenstructure of nonstationary multivariable systems ⋮ On covariance function tests used in system identification

Cites Work

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• A survey of design methods for failure detection in dynamic systems
• Single sample modal identification of a nonstationary stochastic process
• Optimal instrumental variable estimation and approximate implementations
• Uniqueness of the maximum likelihood estimates of the parameters of an ARMA model
• Asymptotic inference in stationary Gaussian time-series
• Sequential detection of abrupt changes in spectral characteristics of digital signals

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