On uniform asymptotic normality of sequential least squares estimators for the parameters in a stable AR(p)

摘要

For a stable autoregressive process of order p with unknown vector parameter theta, it is shown that under a sequential sampling scheme with the stopping time defined by the trace of the observed Fisher information matrix, the least-squares estimator of theta is asymptotically normally distributed uniformly in theta belonging to any compact set in the parameter region. (C) 2003 Elsevier Inc. All rights reserved.