Asymptotic theory for M-estimates in unstable AR(p) processes with infinite variance innovations

被引：1

作者：

Sohrabi, Maryam ^{[1
]}

Zarepour, Mahmoud ^{[1
]}

机构：

[1] Univ Ottawa, Dept Math & Stat, Ottawa, ON, Canada

来源：

JOURNAL OF STATISTICAL PLANNING AND INFERENCE | 2019年 / 198卷

基金：

加拿大自然科学与工程研究理事会;

关键词：

Autoregressive model; Unit root; Stable process; Non-stationary; Bootstrapping; TIME-SERIES; UNIT-ROOT; POINT-PROCESSES; REGRESSION; BOOTSTRAP; TESTS;

D O I：

10.1016/j.jspi.2018.04.001

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：

In this paper, we present the asymptotic distribution of M-estimates for parameters in unstable AR(p) processes. The innovations are assumed to be in the domain of attraction of a symmetric stable law with index 0 < alpha <= 2. In particular, in the case of repeated unit roots or conjugate complex unit roots, M-estimates have a higher asymptotic rate of convergence compared to the least square estimates and the asymptotic results can be written as Ito stochastic integrals. (C) 2018 Elsevier B.V. All rights reserved.

引用

页码：105 / 118

页数：14

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