2019/09/15 by Zhaobo Liu, Liu, Zhaobo, Chanying Li +1 · 1 citation
Engineering · Computer Science · Mathematics · #Control Systems and Identification #Matrix Theory and Algorithms #Statistical Methods and Inference
paper · pdf · doi:10.48550/arxiv.1909.06773
This paper is concerned with the least squares estimator for a basic class of nonlinear autoregressive models, whose outputs are not necessarily to be ergodic. Several asymptotic properties of the least squares estimator have been established under mild conditions. These properties suggest the strong consistency of the least squares estimates in nonlinear autoregressive models which are not divergent.