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arXiv · 1510.02862

Moderate deviations for the mildly stationary autoregressive models with dependent errors

Hui Jiang·Guangyu Yang·Mingming Yu
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Abstract

In this paper, we consider the normalized least squares estimator of the parameter in a mildly stationary first-order autoregressive (AR(1)) model with dependent errors which are modeled as a mildly stationary AR(1) process. By martingale methods, we establish the moderate deviations for the least squares estimators of the regressor and error, which can be applied to understand the near-integrated second order autoregressive processes. As an application, we also obtain the moderate deviations for the Durbin-Watson statistic.

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BibTeXRIS

Hui Jiang, Guangyu Yang, Mingming Yu. 2015-10-10. Moderate deviations for the mildly stationary autoregressive models with dependent errors. https://doi.org/10.1080/02331888.2023.2278034

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