Afrika Statistika

Hellinger Distance Estimation of Strongly Dependent Gaussian Random Fields

Aubin Yao N'DRI, Ouagnina HILI, and Gueï Cyrille OKOU

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Abstract

The Minimum Hellinger Distance Estimator (MHDE) of density function is investigated for stationary long memory (long-range dependent) random fields observed over a finite set of spatial points. A general result on the consistency of the MHD Estimator is first obtained and then, under some mild assumptions, the asymptotic distribution of this estimator is established.

Résumé

L'estimateur du minimum de distance de Hellinger est étudié pour des champs aléatoires stationnaires à longue mémoire observés sur un ensemble fini de points de l'espace. Un résultat général sur la convergence presque sû de cet estimateur est d'abord obtenue, puis, sous certaines hypothèses, la distribution asymptotique est établie.

Article information

Source
Afr. Stat., Volume 14, Number 1 (2019), 1937-1950.

Dates
First available in Project Euclid: 24 May 2019

Permanent link to this document
https://projecteuclid.org/euclid.as/1558664063

Digital Object Identifier
doi:10.16929/as/2019.1937.143

Mathematical Reviews number (MathSciNet)
MR3954232

Zentralblatt MATH identifier
07058651

Subjects
Primary: 60G10: Stationary processes 60G15: Gaussian processes 60G60: Random fields 62F12: Asymptotic properties of estimators

Keywords
asymptotic properties strongly dependence Hellinger distance estimation random field

Citation

N'DRI, Aubin Yao; HILI, Ouagnina; OKOU, Gueï Cyrille. Hellinger Distance Estimation of Strongly Dependent Gaussian Random Fields. Afr. Stat. 14 (2019), no. 1, 1937--1950. doi:10.16929/as/2019.1937.143. https://projecteuclid.org/euclid.as/1558664063


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