TESTING CONDITIONAL INDEPENDENCE VIA ROSENBLATT TRANSFORMS

• 成果类型: Article
• 署名作者: Song, Kyungchul
• 署名单位: University of Pennsylvania
• 刊物名称: ANNALS OF STATISTICS
• ISSN/ISSBN: 0090-5364
• DOI: 10.1214/09-AOS704
• 发表日期: 2009
• 页码: 4011-4045
• 关键词: CENTRAL-LIMIT-THEOREM; serial independence; nonparametric test; regression; entropy; bootstrap; models; checks

摘要

This paper proposes new tests of conditional independence of two random variables given a single-index involving an unknown finite-dimensional parameter. The tests employ Rosenblatt transforms and are shown to be distribution-free while retaining computational convenience. Some results from Monte Carlo simulations are presented and discussed.