A Durbin–Watson serial correlation test for ARX processes via excited adaptive tracking

DOI10.1080/00207179.2015.1052017zbMath1335.62125arXiv1407.3940OpenAlexW1858547393MaRDI QIDQ2799302

Bernard Bercu, Bruno Portier, Victor Vazquez

Publication date: 8 April 2016

Published in: International Journal of Control (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1407.3940

zbMATH Keywords

estimationasymptotic normalityalmost sure convergencepersistent excitationadaptive tracking controlDurbin-Watson statisticstatistical test for serial autocorrelation

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Central limit and other weak theorems (60F05) Adaptive control/observation systems (93C40) Strong limit theorems (60F15) Asymptotic properties of parametric tests (62F05)

Related Items (1)

On the almost sure central limit theorem for ARX processes in adaptive tracking

Cites Work

• Further results on the \(h\)-test of Durbin for stable autoregressive processes
• A new concept of strong controllability via the Schur complement for ARX models in adaptive tracking
• On the asymptotic bias of OLS in dynamic regression models with autocorrelated errors
• Asymptotic distribution of Durbin-Watson statistic
• On the asymptotic behavior of the Durbin-Watson statistic for ARX processes in adaptive tracking
• On the usefulness of persistent excitation in ARX adaptive tracking
• Persistence of excitation in extended least squares
• The AAstrom-Wittenmark self-tuning regulator revisited and ELS-based adaptive trackers
• A sharp analysis on the asymptotic behavior of the Durbin–Watson statistic for the first-order autoregressive process
• TESTING FOR SERIAL CORRELATION IN LEAST SQUARES REGRESSION. II

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