Asymptotic efficiency in the Autoregressive process driven by a stationary Gaussian noise

Marius Soltane

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arXiv · 1810.08805

Asymptotic efficiency in the Autoregressive process driven by a stationary Gaussian noise

Marius Soltane

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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.

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Marius Soltane. 2018-10-20. Asymptotic efficiency in the Autoregressive process driven by a stationary Gaussian noise. https://arxiv.org/abs/1810.08805

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