Asymptotic efficiency in the Autoregressive process driven by a stationary Gaussian noise
Statistics Theory
2018-10-23 v1 Statistics Theory
Abstract
The first purpose of this article is to obtain a.s. asymptotic properties of the maximum likelihood estimator in the autoregressive process driven by a stationary Gaussian noise. The second purpose is to show the local asymptotic normality property of the likelihoods ratio in order to get a notion of asymptotic efficiency and to build an asymptotically uniformly invariant most powerful procedure for testing the significance of the autoregressive parameter.
Keywords
Cite
@article{arxiv.1810.08805,
title = {Asymptotic efficiency in the Autoregressive process driven by a stationary Gaussian noise},
author = {Marius Soltane},
journal= {arXiv preprint arXiv:1810.08805},
year = {2018}
}