Asymptotics of self-weighted M-estimators for autoregressive models

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• 作者：Xinghui Wang ; Shuhe Hu
• 关键词：Self ; weighted M ; estimator ; Autoregressive model ; Stationary process ; Infinite variance
• 刊名：Metrika
• 出版年：2017
• 出版时间：January 2017
• 年：2017
• 卷：80
• 期：1
• 页码：83-92
• 全文大小：
• 刊物类别：Mathematics and Statistics
• 刊物主题：Statistics, general; Statistics for Business/Economics/Mathematical Finance/Insurance; Probability Theory and Stochastic Processes; Economic Theory/Quantitative Economics/Mathematical Methods;
• 出版者：Springer Berlin Heidelberg
• ISSN：1435-926X
• 卷排序：80

文摘

In this paper, we consider a stationary autoregressive AR(p) time series \(y_t=\phi _0+\phi _1y_{t-1}+\cdots +\phi _{p}y_{t-p}+u_t\). A self-weighted M-estimator for the AR(p) model is proposed. The asymptotic normality of this estimator is established, which includes the asymptotic properties under the innovations with finite or infinite variance. The result generalizes and improves the known one in the literature.