Model selection in irregular problems: Applications to mapping quantitative trait loci

• 成果类型: Article
• 署名作者: Siegmund, D
• 署名单位: Stanford University
• 刊物名称: BIOMETRIKA
• ISSN/ISSBN: 0006-3444
• DOI: 10.1093/biomet/91.4.785
• 发表日期: 2004
• 页码: 785800
• 关键词: high-resolution maps; Linkage analysis; statistical-methods; IDENTITY; probabilities; tests

摘要

Two methods of model selection are discussed for changepoint-like problems, especially those arising in genetic linkage analysis. The first is a method that selects the model with the smallest p-value, while the second is a modification of the Bayes information criterion. The methods are compared theoretically and on examples from the literature. For these examples, they are roughly comparable although the p-value-based method is somewhat more liberal in selecting a high-dimensional model.