A Durbin-Watson serial correlation test for ARX processes via excited adaptive tracking
Probability
2014-07-16 v1 Statistics Theory
Statistics Theory
Abstract
We propose a new statistical test for the residual autocorrelation in ARX adaptive tracking. The introduction of a persistent excitation in the adaptive tracking control allows us to build a bilateral statistical test based on the well-known Durbin-Watson statistic. We establish the almost sure convergence and the asymptotic normality for the Durbin-Watson statistic leading to a powerful serial correlation test. Numerical experiments illustrate the good performances of our statistical test procedure.
Cite
@article{arxiv.1407.3940,
title = {A Durbin-Watson serial correlation test for ARX processes via excited adaptive tracking},
author = {Bernard Bercu and Bruno Portier and Victor Vazquez},
journal= {arXiv preprint arXiv:1407.3940},
year = {2014}
}