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Subsampling inference for the mean in the heavy-tailed case

✍ Scribed by Joseph P. Romano; Michael Wolf


Book ID
105857055
Publisher
Springer
Year
1999
Tongue
English
Weight
141 KB
Volume
50
Category
Article
ISSN
0026-1335

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Inference for the mean difference in the two-sample random censorship model is an important problem in comparative survival and reliability test studies. This paper develops an adjusted empirical likelihood inference and a martingale-based bootstrap inference for the mean difference. A nonparametric