CHANGE-POINT DETECTION WITH RANK STATISTICS IN LONG-MEMORY TIME-SERIES MODELS

Lihong Wang

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CHANGE-POINT DETECTION WITH RANK STATISTICS IN LONG-MEMORY TIME-SERIES MODELS

机译：长记忆时间序列模型中具有秩统计量的变化点检测

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摘要

Wilcoxon-type rank statistics are considered for testing a long-memory time-series model with a common distribution against the alternatives involving a change in the distribution at an unknown time point. The asymptotic properties of the test statistics and the change-point estimators are studied. Finite-sample behaviours are investigated in a small Monte Carlo simulation study. Data examples from hydrology and telecommunications illustrate the method.

机译：考虑使用Wilcoxon型秩统计来测试具有共同分布的长记忆时间序列模型，而不涉及涉及未知时间点分布变化的备选方案。研究了检验统计量和变化点估计量的渐近性质。在一个小型蒙特卡洛模拟研究中研究了有限样本行为。来自水文和电信的数据示例说明了该方法。

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《Australian & New Zealand journal of statistics》 |2008年第3期|p.241-256|共16页
作者
Lihong Wang;
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作者单位

Nanjing University;

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原文格式 PDF
正文语种 eng
中图分类统计学;
关键词
change-point analysis; long-memory process; rank statistics;

机译：变更点分析;长记忆过程;等级统计;

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CHANGE-POINT DETECTION WITH RANK STATISTICS IN LONG-MEMORY TIME-SERIES MODELS

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