Moderate deviation principle for autoregressive processes
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].
Year of publication: |
2009
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Authors: | Yu, Miao ; Si, Shen |
Published in: |
Journal of Multivariate Analysis. - Elsevier, ISSN 0047-259X. - Vol. 100.2009, 9, p. 1952-1961
|
Publisher: |
Elsevier |
Keywords: | Moderate deviation Autoregressive processes Least squares estimator Yule-Walker estimator |
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