Control Charts for Dependent and Independent Measurements Based on Bootstrap Methods
作者:
ReginaY. Liu,
Jen Tang,
期刊:
Journal of the American Statistical Association
(Taylor Available online 1996)
卷期:
Volume 91,
issue 436
页码: 1694-1700
ISSN:0162-1459
年代: 1996
DOI:10.1080/01621459.1996.10476740
出版商: Taylor & Francis Group
关键词: Dependent processes;Moving blocks bootstrap;Nonparametric process control;Shewhart charts
数据来源: Taylor
摘要:
Shewhart charts are widely accepted as standard tools for monitoring manufacturing processes of univariate, independent “nearly” normal measurements. They are not as well developed beyond these types of data. We generalize the idea of Shewhart charts to cover other types of data commonly encountered in practice. More specifically, we develop some valid control charts for dependent data and for independent data that are not necessarily “nearly” normal. We derive the proposed charts from the moving blocks bootstrap and the standard bootstrap methods. Their constructions are completely nonparametric no distributional assumptions are required. Some simulated as well as real data examples are included they are very supportive of the proposed methods.
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