置信区间
重采样
流程图
计算机科学
统计
置信分布
稳健置信区间
优势和劣势
图表
基于CDF的非参数置信区间
数据挖掘
数学
人工智能
心理学
工程类
工程制图
社会心理学
作者
James R. Carpenter,John F. Bithell
标识
DOI:10.1002/(sici)1097-0258(20000515)19:9<1141::aid-sim479>3.0.co;2-f
摘要
Since the early 1980s, a bewildering array of methods for constructing bootstrap confidence intervals have been proposed. In this article, we address the following questions. First, when should bootstrap confidence intervals be used. Secondly, which method should be chosen, and thirdly, how should it be implemented. In order to do this, we review the common algorithms for resampling and methods for constructing bootstrap confidence intervals, together with some less well known ones, highlighting their strengths and weaknesses. We then present a simulation study, a flow chart for choosing an appropriate method and a survival analysis example.
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