Nonparametric checks for single-index models

• 成果类型: Article
• 署名作者: Stute, W; Zhu, LX
• 署名单位: Justus Liebig University Giessen; University of Hong Kong
• 刊物名称: ANNALS OF STATISTICS
• ISSN/ISSBN: 0090-5364
• DOI: 10.1214/009053605000000020
• 发表日期: 2005
• 页码: 1048-1083
• 关键词: GENERALIZED LINEAR-MODELS; of-fit tests; oscillation behavior; REGRESSION FUNCTION; Empirical Processes; GOODNESS; adequacy

摘要

In this paper we study goodness-of-fit testing of single-index models. The large sample behavior of certain score-type test statistics is investigated. As a by-product, we obtain asymptotically distribution-free maximin tests for a large class of local alternatives. Furthermore, characteristic function based goodness-of-fit tests are proposed which are omnibus and able to detect peak alternatives. Simulation results indicate that the approximation through the limit distribution is acceptable already for moderate sample sizes. Applications to two real data sets are illustrated.