VALIDITY OF BLOCKWISE BOOTSTRAP FOR EMPIRICAL PROCESSES WITH STATIONARY OBSERVATIONS

• 成果类型: Article
• 署名作者: NAIKNIMBALKAR, UV; RAJARSHI, MB
• 刊物名称: ANNALS OF STATISTICS
• ISSN/ISSBN: 0090-5364
• DOI: 10.1214/aos/1176325507
• 发表日期: 1994
• 页码: 980-994
• 关键词: estimators; SEQUENCES

摘要

We show that the empirical process of the block-based bootstrap observations from a stationary sequence converges weakly to an appropriate Gaussian process, conditionally in probability and almost surely depending upon the block length. This bootstrap was introduced by Kunsch and later by Liu and Singh. Applications in estimation of the sampling distribution of a compactly differentiable functional are indicated.