Testing for change points in time series models and limiting theorems for ned sequences

• 成果类型: Article
• 署名作者: Ling, Shiqing
• 署名单位: Hong Kong University of Science & Technology
• 刊物名称: ANNALS OF STATISTICS
• ISSN/ISSBN: 0090-5364
• DOI: 10.1214/009053606000001514
• 发表日期: 2007
• 页码: 1213-1237
• 关键词: invariance-principles; INEQUALITY; sums

摘要

This paper first establishes a strong law of large numbers and a strong invariance principle for forward and backward sums of near-epoch dependent sequences. Using these limiting theorems, we develop a general asymptotic theory on the Wald test for change points in a general class of time series models under the no change-point hypothesis. As an application, we verify our assumptions for the long-memory fractional ARIMA model.