Alternative Goodness-of-Fit Tests for Linear Models

• 成果类型: Article
• 署名作者: Christensen, Ronald; Sun, Siu Kei
• 署名单位: University of New Mexico
• 刊物名称: JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION
• ISSN/ISSBN: 0162-1459
• DOI: 10.1198/jasa.2009.tm08697
• 发表日期: 2010
• 页码: 291-301
• 关键词: regression

摘要

Fan and Huang (2001) presented a goodness-of-fit test for linear models based on Fourier transformations of the residuals of the fitted model We present two mole theoretically appealing tests in which the Fourier transforms are incorporated into a tilted model We show that when suitably normalized. the new test statistics have the same as distribution as Fan and Huang's test We propose modifications to the asymptotic normalization constants to improve the small sample sizes of our tests while retaining their asymptotic distributions Small sample sizes and powers are examined via simulations An illustration is given