Detection of changes in the characteristics of oceanographic time-series using changepoint analysis.
Detection of changes in the characteristics of oceanographic time-series using changepoint analysis.
复制标题
使用变点分析检测海洋时间序列特征的变化。
DOI：
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发表时间：
2010
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通讯作者：
K. Ewans
中科院分区：
文献类型：
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作者：
Rebecca Killick;I. Eckley;P. Jonathan;K. Ewans
变点分析用于检测 GOMOS 后报时间序列中 1900-2005 年期间墨西哥湾风暴峰值事件的重要波高的变异性变化。为了检测方差的变化，两步过程包括 (1) 验证每个地理位置的模型假设，然后 (2) 应用惩罚似然变化点算法。结果表明，时间序列方差最重要的变化发生在 1916 年和 1933 年，发生在边界位置的小簇上，一般来说，方差会减小。没有检测到战后变化点。变点过程可以很容易地应用于其他环境时间序列。
Changepoint analysis is used to detect changes in variability within GOMOS hindcast time-series for significant wave heights of storm peak events across the Gulf of Mexico for the period 1900–2005. To detect a change in variance, the two-step procedure consists of (1) validating model assumptions per geographic location, followed by (2) application of a penalized likelihood changepoint algorithm. Results suggest that the most important changes in time-series variance occur in 1916 and 1933 at small clusters of boundary locations at which, in general, the variance reduces. No post-war changepoints are detected. The changepoint procedure can be readily applied to other environmental time-series.