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在时间序列变化的依赖结构建模的产品分配模型

Product Partition Models for Modelling Changing Dependency Structure in Time Series
课程网址: http://videolectures.net/nipsworkshops09_murphy_ppmmcdsts/  
主讲教师: Kevin P. Murphy
开课单位: 谷歌公司
开课时间: 2010-01-19
课程语种: 英语
中文简介:
我们展示了如何在多变量环境中应用Fearnhead的高效贝叶斯变换点检测技术。我们使用无向高斯图模型模拟矢量值观测的联合密度,我们估计其结构。我们展示了如何精确计算MAP分割,以及如何从后分割中绘制完美样本,同时考虑变化点的数量和位置的不确定性,以及协方差结构的不确定性。我们通过将其应用于财务数据和蜜蜂跟踪数据来说明该技术。
课程简介: We show how to apply the efficient Bayesian changepoint detection techniques of Fearnhead in the multivariate setting. We model the joint density of vector-valued observations using undirected Gaussian graphical models, whose structure we estimate. We show how we can exactly compute the MAP segmentation, as well as how to draw perfect samples from the posterior over segmentations, simultaneously accounting for uncertainty about the number and location of changepoints, as well as uncertainty about the covariance structure. We illustrate the technique by applying it to financial data and to bee tracking data.
关 键 词: 贝叶斯变点检测技术; 无向高斯的图形化模型; 产品分配模型
课程来源: 视频讲座网
最后编审: 2020-06-01:吴雨秋(课程编辑志愿者)
阅读次数: 90