ASYMPTOTIC EFFICIENCY IN THE AUTOREGRESSIVE PROCESS DRIVEN BY A STATIONARY GAUSSIAN NOISE - Archive ouverte HAL
Pré-Publication, Document De Travail Année : 2018

ASYMPTOTIC EFFICIENCY IN THE AUTOREGRESSIVE PROCESS DRIVEN BY A STATIONARY GAUSSIAN NOISE

Marius Soltane

Résumé

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.
Fichier principal
Vignette du fichier
article_MLE3.pdf (362.98 Ko) Télécharger le fichier
Origine Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-01899971 , version 1 (20-10-2018)

Identifiants

  • HAL Id : hal-01899971 , version 1

Citer

Marius Soltane. ASYMPTOTIC EFFICIENCY IN THE AUTOREGRESSIVE PROCESS DRIVEN BY A STATIONARY GAUSSIAN NOISE. 2018. ⟨hal-01899971⟩
811 Consultations
113 Téléchargements

Partager

More