Title of article
Moderate deviation principle for autoregressive processes
Author/Authors
Yu، نويسنده , , Miao and Si، نويسنده , , Shen، نويسنده ,
Issue Information
دوفصلنامه با شماره پیاپی سال 2009
Pages
10
From page
1952
To page
1961
Abstract
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. Poincaré-PR 42 (2006) 393–416].
Keywords
Yule–Walker estimator , Moderate deviation , Autoregressive processes , Least squares estimator
Journal title
Journal of Multivariate Analysis
Serial Year
2009
Journal title
Journal of Multivariate Analysis
Record number
1565195
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