On the least squares estimator in a nearly unstable sequence of stationary spatial AR models

被引：4

作者：

Baran, Sandor ^{[1
]}

Pap, Gyula ^{[1
]}

机构：

[1] Univ Debrecen, Fac Informat, H-4010 Debrecen, Hungary

来源：

JOURNAL OF MULTIVARIATE ANALYSIS | 2009年 / 100卷 / 04期

基金：

匈牙利科学研究基金会;

关键词：

Autoregressive model; Asymptotic normality; Martingale central limit theorem; ASYMPTOTIC INFERENCE; UNIT ROOTS; AUTOREGRESSION;

D O I：

10.1016/j.jmva.2008.07.003

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 nearly unstable sequence of stationary spatial autoregressive processes is investigated, when the sum of the absolute values of the autoregressive coefficients tends to one. It is shown that after an appropriate normalization the least squares estimator for these coefficients has a normal limit distribution. If none of the parameters equals zero then the typical rate of convergence is n. (C) 2008 Elsevier Inc. All rights reserved.

引用

页码：686 / 698

页数：13

共 5 条

[1] Asymptotic inference for a nearly unstable sequence of stationary spatial AR models
Baran, S
Pap, G
van Zuijlen, MCA
STATISTICS & PROBABILITY LETTERS, 2004, 69 (01) : 53 - 61
[2] THE LIMITING DISTRIBUTION OF THE LEAST-SQUARES ESTIMATOR IN NEARLY INTEGRATED SEASONAL MODELS
PERRON, P
CANADIAN JOURNAL OF STATISTICS-REVUE CANADIENNE DE STATISTIQUE, 1992, 20 (02): : 121 - 134
[3] Infill Asymptotics Inside Increasing Domains for the Least Squares Estimator in Linear Models
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[4] Asymptotic normality of the time-domain generalized least squares estimator for linear regression models
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STAT, 2019, 8 (01):
[5] MOMENT APPROXIMATION FOR LEAST-SQUARES ESTIMATOR IN FIRST-ORDER REGRESSION MODELS WITH UNIT ROOT AND NONNORMAL ERRORS
Bao, Yong
Ullah, Aman
Zhang, Ru
ESSAYS IN HONOR OF PETER C. B. PHILLIPS, 2014, 33 : 65 - 92

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