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2013,High-dimensional Covariance Estimation: with High-Dimensional Data pdf

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  • TA的每日心情
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    2016-3-19 06:18
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    [LV.4]偶尔看看III

    发表于 2014-8-14 13:54:47 | 显示全部楼层 |阅读模式
    Mohsen Pourahmadi, "High-dimensional Covariance Estimation: with High-Dimensional Data"
    English | ISBN: 1118034295 | 2014 | 208 pages | PDF | 6 MB
    高清版本pdf 回复可见
    游客,如果您要查看本帖隐藏内容请回复

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    Methods for estimating sparse and large covariance matrices Covariance and correlation matrices play fundamental roles in every aspect of the analysis of multivariate data collected from a variety of fields including business and economics, health care, engineering, and environmental and physical sciences. High–Dimensional Covariance Estimation provides accessible and comprehensive coverage of the classical and modern approaches for estimating covariance matrices as well as their applications to the rapidly developing areas lying at the intersection of statistics and machine learning. Recently, the classical sample covariance methodologies have been modified and improved upon to meet the needs of statisticians and researchers dealing with large correlated datasets. High–Dimensional Covariance Estimation focuses on the methodologies based on shrinkage, thresholding, and penalized likelihood with applications to Gaussian graphical models, prediction, and mean–variance portfolio management. The book relies heavily on regression–based ideas and interpretations to connect and unify many existing methods and algorithms for the task. High–Dimensional Covariance Estimation features chapters on: Data, Sparsity, and Regularization Regularizing the Eigenstructure Banding, Tapering, and Thresholding Covariance Matrices Sparse Gaussian Graphical Models Multivariate Regression The book is an ideal resource for researchers in statistics, mathematics, business and economics, computer sciences, and engineering, as well as a useful text or supplement for graduate–level courses in multivariate analysis, covariance estimation, statistical learning, and high–dimensional data analysis.




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  • TA的每日心情
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    2015-2-14 16:25
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    [LV.5]常住居民I

    发表于 2015-11-26 02:20:11 | 显示全部楼层
    很经典。
    谢谢。
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  • TA的每日心情
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    2017-12-15 11:07
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    [LV.7]常住居民III

    发表于 2016-2-13 13:51:20 | 显示全部楼层
    谢谢楼主辛苦分享!!
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    该用户从未签到

    发表于 2016-12-2 10:49:26 | 显示全部楼层
    Thanks a lot.

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  • TA的每日心情
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    3 小时前
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    [LV.10]以坛为家III

    发表于 2017-2-3 17:40:15 | 显示全部楼层
    感谢楼主辛苦分享!!
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  • TA的每日心情
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    2017-8-21 10:57
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    [LV.1]初来乍到

    发表于 2017-7-25 19:04:16 | 显示全部楼层
    6666666666666666
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  • TA的每日心情
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    2013-11-11 23:43
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    [LV.1]初来乍到

    发表于 2018-4-24 14:09:55 | 显示全部楼层
    need to learn this topic
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    发表于 2018-9-15 16:12:12 | 显示全部楼层
    好好学学,谢谢分享
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