Nonparametric model checks for regression

• 成果类型: Article
• 署名作者: Stute, W
• 署名单位: Justus Liebig University Giessen
• 刊物名称: ANNALS OF STATISTICS
• ISSN/ISSBN: 0090-5364
• 发表日期: 1997
• 页码: 613-641
• 关键词: GOODNESS-OF-FIT; Weak Convergence; asymptotic power; cramer-vonmises; linear-model; diagnostics; CURVES; Cusum; tests

摘要

In this paper we study a marked empirical process based on residuals. Results on its large-sample behavior may be used to provide nonparametric full-model checks for regression. Their decomposition into principal components gives new insight into the question: which kind of departure from a hypothetical model may be well detected by residual-based goodness-of-fit methods? The work also contains a small simulation study on straight-line regression.