M-estimation of linear models with dependent errors

• 成果类型: Article
• 署名作者: Wu, Wei Biao
• 署名单位: University of Chicago
• 刊物名称: ANNALS OF STATISTICS
• ISSN/ISSBN: 0090-5364
• DOI: 10.1214/009053606000001406
• 发表日期: 2007
• 页码: 495-521
• 关键词: iterated random functions; variance moving averages; INFINITE-VARIANCE; Asymptotic Normality; Robust Estimation; bahadur representation; regression parameters; random-variables; LIMIT-THEOREMS; quantiles

摘要

We study asymptotic properties of M-estimates of regression parameters in linear models in which errors are dependent. Weak and strong Bahadur representations of the M-estimates are derived and a central limit theorem is established. The results are applied to linear models with errors being short-range dependent linear processes, heavy-tailed linear processes and some widely used nonlinear time series.