Nonparametric model checks for time series

• 成果类型: Article
• 署名作者: Koul, HL; Stute, W
• 署名单位: Michigan State University; Justus Liebig University Giessen
• 刊物名称: ANNALS OF STATISTICS
• ISSN/ISSBN: 0090-5364
• 发表日期: 1999
• 页码: 204-236
• 关键词: WEAK-CONVERGENCE; tests

摘要

This paper studies a class of tests useful for testing the goodness-of-fit of an autoregressive model. These tests are based on a class of empirical processes marked by certain residuals. The paper first gives their large sample behavior under null hypotheses. Then a martingale transformation of the underlying process is given that makes tests based on it asymptotically distribution free. Consistency of these tests is also discussed briefly.