Adaptive confidence balls
成果类型:
Article
署名作者:
Cai, TT; Low, MG
署名单位:
University of Pennsylvania
刊物名称:
ANNALS OF STATISTICS
ISSN/ISSBN:
0090-5364
DOI:
10.1214/009053606000000146
发表日期:
2006
页码:
202-228
关键词:
wavelet regression
sets
estimators
摘要:
Adaptive confidence balls are constructed for individual resolution levels as well as the entire mean vector in a multiresolution framework. Finite sample lower bounds are given for the minimum expected squared radius for confidence balls with a prespecified confidence level. The confidence balls are centered on adaptive estimators based on special local block thresholding rules. The radius is derived from an analysis of the loss of this adaptive estimator. In addition adaptive honest confidence balls are constructed which have guaranteed coverage probability over all of RN and expected squared radius adapting over a maximum range of Besov bodies.
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