Moderate deviation principle for autoregressive processes

JOURNAL OF MULTIVARIATE ANALYSIS

卷:100

Article

Miao, Yu¹  Shen, Si² 

[1] Henan Normal Univ, Coll Math & Informat Sci, Xinxiang 453007, Henan, Peoples R China

[2] Cent Univ Nationalities, Dept Stat, Coll Sci, Beijing 100081, Peoples R China

关键词: Moderate deviation;    Autoregressive processes;    Least squares estimator;    Yule-Walker estimator;   

DOI  :  10.1016/j.jmva.2009.06.005

来源: Elsevier

【 摘 要 】

A moderate deviation principle for autoregressive processes is established. As statistical applications we provide the moderate deviation estimates of the least square and the Yule-Walker estimators of the parameter of an autoregressive process. The main assumption on the autoregressive process is the Gaussian integrability condition for the noise, which is weaker than the assumption of Logarithmic Sobolev Inequality in [H. Djellout, A. Guillin, L. Wu, Moderate deviations of empirical periodogram and nonlinear functionals of moving average processes, Ann. I. H. Poincare-PR 42 (2006) 393-416]. (C) 2009 Elsevier Inc. All rights reserved.

【 授权许可】

Free