Testing for differences between conditional means in a time series context

• 成果类型: Article
• 署名作者: Ferreira, E; Stute, W
• 署名单位: University of Basque Country; Justus Liebig University Giessen
• 刊物名称: JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION
• ISSN/ISSBN: 0162-1459
• DOI: 10.1198/016214504000000160
• 发表日期: 2004
• 页码: 169-174
• 关键词: nonparametric regression-curves; glivenko-cantelli theorem; EQUALITY

摘要

In this article we study tests for equality of two regression curves when the inputs are driven by a time series. The basic process underlying the test statistics is the empirical process of the time series marked by the difference in the pertaining dependent variables. The main results hold under strict stationarity of the input variables, but no mixing condition or special modeling of the time series will be necessary. A simulation study is reported on, which illustrates the quality of the distributional approximation and the power of the tests for small to moderate sample sizes. An application to a real dataset is also included.