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Joint segmentation of multivariate Gaussian processes using mixed linear models

机译:使用混合线性模型对多元高斯过程进行联合分割

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摘要

The joint segmentation of multiple series is considered. A mixed linear model is used to account for both covariates and correlations between signals. An estimation algorithm based on EM which involves a new dynamic programming strategy for the segmentation step is proposed. The computational efficiency of this procedure is shown and its performance is assessed through simulation experiments. Applications are presented in the field of climatic data analysis.
机译:考虑多个系列的联合分割。混合线性模型用于说明信号之间的协变量和相关性。提出了一种基于EM的估计算法,该算法为分割步骤引入了一种新的动态规划策略。显示了此过程的计算效率,并通过模拟实验评估了其性能。在气候数据分析领域中介绍了应用程序。

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