On the asymptotic behavior of the Durbin-Watson statistic for ARX processes in adaptive tracking

DOI10.1002/ACS.2424zbMath1337.93087arXiv1204.4677OpenAlexW1907749210MaRDI QIDQ2802047

Bernard Bercu, Bruno Portier, Victor Vazquez

Publication date: 22 April 2016

Published in: International Journal of Adaptive Control and Signal Processing (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1204.4677

zbMATH Keywords

estimationadaptive controlcentral limit theoremalmost sure convergenceDurbin-Watson statisticstatistical test for serial autocorrelation

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Adaptive control/observation systems (93C40) Estimation and detection in stochastic control theory (93E10) Least squares and related methods for stochastic control systems (93E24) Identification in stochastic control theory (93E12)

Related Items (3)

Robust identification of OE model with constrained output using optimal input design ⋮ On the almost sure central limit theorem for ARX processes in adaptive tracking ⋮ A Durbin–Watson serial correlation test for ARX processes via excited adaptive tracking

Cites Work

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• On the asymptotic bias of OLS in dynamic regression models with autocorrelated errors
• Estimation et prevision dans les modeles economiques autoregressifs
• 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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