On least squares estimation for long-memory lattice processes

被引：28

作者：

Beran, Jan ^{[1
]}

Ghosh, Sucharita

Schell, Dieter ^{[1
]}

机构：

[1] Univ Konstanz, Dept Math & Stat, D-7750 Constance, Germany

来源：

JOURNAL OF MULTIVARIATE ANALYSIS | 2009年 / 100卷 / 10期

关键词：

Long memory; Fractional ARIMA process; Lattice process; Maximum likelihood estimation; Anisotropy; MAXIMUM-LIKELIHOOD-ESTIMATION; PARAMETER-ESTIMATION; WHITTLE ESTIMATION; STATIONARY; RANGE; MODELS; FIELDS; NOISE;

D O I：

10.1016/j.jmva.2009.04.007

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

A flexible class of anisotropic stationary lattice processes with long memory can be defined in terms of a two-way fractional ARIMA (FARIMA) representation. We consider parameter estimation based on minimizing an approximate residual sum of squares. The method can be applied to sampling areas that are not necessarily rectangular. A central limit theorem is derived under general conditions. The method is illustrated by an analysis of satellite data consisting of total column ozone amounts in Europe and the Atlantic respectively. (C) 2009 Elsevier Inc. All rights reserved.

引用

页码：2178 / 2194

页数：17

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