April 2021 Parametric Estimation of Long Memory Multivariate Gaussian random fields
Aubin Yao N’DRI, Amadou KAMAGATÉ, Ouagnina HILI
Afr. Stat. 16(2): 2749-2766 (April 2021). DOI: 10.16929/as/2021.2749.182

Abstract

The aim of this paper is to make a theoretically study of the minimum Hellinger distance estimator of multivariate, gaussian, stationary, isotropic long-memory random fields The variables are observed on a finite set of points in space. We establish under certain assumptions, the almost sure convergence and the asymptotic distribution of this estimator.

Le but de ce papier est d'étudier de façon théorique l'estimateur du minimum de distance de Hellinger des champs aléatoires multivariés, gaussiens, stationnaires, isotropes à longue mémoire.Les variables sont observées sur un ensemble fini de points de l'espace. Nous établissons sous certaines conditions, la convergence presque sûre et la distribution asymptotique de cet estimateur.

Citation

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Aubin Yao N’DRI. Amadou KAMAGATÉ. Ouagnina HILI. "Parametric Estimation of Long Memory Multivariate Gaussian random fields." Afr. Stat. 16 (2) 2749 - 2766, April 2021. https://doi.org/10.16929/as/2021.2749.182

Information

Published: April 2021
First available in Project Euclid: 5 November 2021

Digital Object Identifier: 10.16929/as/2021.2749.182

Subjects:
Primary: 60G10
Secondary: 60G15 , 60G60 , 62F12

Keywords: asymptotic properties , multivariate long memory , Random field

Rights: Copyright © 2021 The Statistics and Probability African Society

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Vol.16 • No. 2 • April 2021
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