时间序列的渐近统计分析:聚类、变点和其它问题Asymptotic Statistical Analysis of Time Series: Clustering, Change Point, and Other Problems |
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课程网址: | http://videolectures.net/onlinelearning2012_ryabko_time_series/ |
主讲教师: | Daniil Ryabko |
开课单位: | INRIA研究机构 |
开课时间: | 2013-05-28 |
课程语种: | 英语 |
中文简介: | 提出了一种构造平稳遍历时间序列各种统计问题渐近一致有效算法的方法。所考虑的问题包括聚类、假设检验、变点估计等。该方法基于分布距离的经验估计。还讨论了一些尚未解决的问题。 |
课程简介: | A method for constructing asymptotically consistent efficient algorithms for various statistical problems concerning stationary ergodic time series is presented. The considered problems include clustering, hypothesis testing, change-point estimation and others. The presented approach is based on empirical estimates ofthe distributional distance. Some open problems are also discussed. |
关 键 词: | 统计问题; 时间序列; 聚类; 假设检验; 变点估计 |
课程来源: | 视频讲座网 |
最后编审: | 2021-01-08:yumf |
阅读次数: | 51 |