Inference of trends in time series

• 成果类型: Article
• 署名作者: Wu, Wei Biao; Zhao, Zhibiao
• 署名单位: University of Chicago
• 刊物名称: JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY
• ISSN/ISSBN: 1369-7412
• DOI: 10.1111/j.1467-9868.2007.00594.x
• 发表日期: 2007
• 页码: 391-410
• 关键词: Nonparametric regression; confidence bands; kernel regression; change-points; bootstrap; estimators; deviations; dependence; bandwidth; variance

摘要

We consider statistical inference of trends in mean non-stationary models. A test statistic is proposed for the existence of structural breaks in trends. On the basis of a strong invariance principle of stationary processes, we construct simultaneous confidence bands with asymptotically correct nominal coverage probabilities. The results are applied to global warming temperature data and Nile river flow data. Our confidence band of the trend of the global warming temperature series supports the claim that the trend is increasing over the last 150 years.