Stationary Bootstrap for U-Statistics under Strong Mixing

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초록

Validity of the stationary bootstrap of Politis and Romano (1994) is proved for U-statistics under strong mixing. Weak and strong consistencies are established for the stationary bootstrap of U-statistics. The theory is applied to a symmetry test which is a U-statistic regarding a kernel density estimator. The theory enables the bootstrap confidence intervals of the means of the U-statistics. A Monte-Carlo experiment for bootstrap confidence intervals confirms the asymptotic theory.

키워드

Stationary bootstrapU-statisticstrong mixingstrong consistencyweak consistencyMonte Carlo study
제목
Stationary Bootstrap for U-Statistics under Strong Mixing
저자
Hwang, EunjuShin, Dong Wan
DOI
10.5351/CSAM.2015.22.1.081
발행일
2015-01
유형
Article
저널명
Communications for Statistical Applications and Methods
22
1
페이지
81 ~ 93