Testing goodness-of-fit based on a roughness measure

• 成果类型: Article
• 署名作者: Huang, LS
• 刊物名称: JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION
• ISSN/ISSBN: 0162-1459
• DOI: 10.2307/2965409
• 发表日期: 1997
• 页码: 1399-1402
• 关键词: density; estimators; models; POWER

摘要

A test for the one-sample goodness-of-fit problem is proposed. The test is based on a distance that measures the difference, in terms of roughness, between the underlying density function and the hypothesized density function. One advantage of using a roughness measure is high power in detecting high-frequency alternatives and densities with sharp features. The test statistic that estimates the distance is derived from the viewpoint of kernel density estimation, and a testing procedure is developed based on the asymptotic distribution of the test statistic. The proposed test is compared to the Kolmogorov-Smirnov test.