Statistics Theory and Methods

[1] Association Pattern Discovery via Theme Dictionary Models

Ke Deng Tsinghua University Zhi Geng Peking University Jun S. Liu Harvard University

Statistics Theory and Methods mathscidoc:1904.33003

Journal of the Royal Statistical Society, Series B, 76, (2), 319–347, 2014
[ Download ] [ 2019-04-30 09:39:50 uploaded by KeDeng ] [ 7 downloads ] [ 0 comments ] [ Abstract ] [ Full ]
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[2] Bayesian Aggregation of Order-Based Rank Data

Ke Deng Tsinghua University Simeng Han Harvard University Kate J. Li Suffolk University Jun S. Liu Harvard University

Statistics Theory and Methods mathscidoc:1904.33002

Journal of the American Statistical Association, 109, (507), 1023-1039, 2014
[ Download ] [ 2019-04-30 09:38:14 uploaded by KeDeng ] [ 14 downloads ] [ 0 comments ] [ Abstract ] [ Full ]
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[3] On the Unsupervised Analysis of Domain-Specific Chinese Texts

Ke Deng Tsinghua University Peter K. Bol Harvard University Kate J. Li Suffolk University Jun S. Liu Harvard University

Statistics Theory and Methods mathscidoc:1904.33001

PNAS, 113, (22), 6154-6159, 2016
[ Download ] [ 2019-04-30 09:35:35 uploaded by KeDeng ] [ 6 downloads ] [ 0 comments ] [ Abstract ] [ Full ]
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[4] Feature Selection for Varying Coefficient Models With Ultrahigh-Dimensional Covariates

Jingyuan Liu Xiamen University

Statistics Theory and Methods mathscidoc:1903.33002

Journal of the American Statistical Association, 109, (505), 266-274, 2014.3
[ Download ] [ 2019-03-21 09:38:42 uploaded by jingyuan1230 ] [ 18 downloads ] [ 0 comments ] [ Abstract ] [ Full ]
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[5] Model-Free Feature Screening for Ultrahigh Dimensional Discriminant Analysis

Hengjian Cui Capital Normal University Runze Li Pennsylvania State University Wei Zhong Xiamen University

Statistics Theory and Methods mathscidoc:1903.33001

Journal of the American Statistical Association, 110, (510), 630-641, 2015.6
[ Download ] [ 2019-03-19 22:55:01 uploaded by wzhong41 ] [ 13 downloads ] [ 0 comments ] [ Abstract ] [ Full ]
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[6] Necessary and sufficient conditions for consistent root reconstruction in Markov models on trees

Wai Tong Fan UW-Madison

Information Theory Probability Statistics Theory and Methods mathscidoc:1806.19001

Electronic Journal of Probability, 23, (47), 24, 2018
[ Download ] [ 2018-06-19 02:42:52 uploaded by louisfan ] [ 142 downloads ] [ 0 comments ] [ Abstract ] [ Full ]
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[7] Large Covariance Estimation by Thresholding Principal Orthogonal Complements

Jianqing Fan Princeton University Yuan Liao Princeton University Martina Mincheva University of Maryland

Statistics Theory and Methods mathscidoc:1806.33003

Journal of the Royal Statistical Society, 2013
[ Download ] [ 2018-06-11 17:15:57 uploaded by YLiao ] [ 146 downloads ] [ 0 comments ] [ Abstract ] [ Full ]
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[8] Confidence intervals for low dimensional parameters in high dimensional linear models

Cun-Hui Zhang Rutgers University Stephanie S. Zhang Columbia University

Statistics Theory and Methods mathscidoc:1806.33002

Journal of the Royal Statistical Society, 76, 217-242, 2014
[ Download ] [ 2018-06-11 09:41:36 uploaded by CHZhang ] [ 345 downloads ] [ 0 comments ] [ Abstract ] [ Full ]
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[9] A useful variant of the Davis--Kahan theorem for statisticians.

Yi Yu University of Bristol Tengyao Wang University of Cambridge Richard J. Samworth University of Cambridge

Statistics Theory and Methods mathscidoc:1806.33001

Biometrika, 102, 315-323
[ Download ] [ 2018-06-07 16:56:33 uploaded by yy15165 ] [ 123 downloads ] [ 0 comments ] [ Abstract ] [ Full ]
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[10] The ZD-GARCH model: A new way to study heteroscedasticity

Dong Li Tsinghua University

Statistics Theory and Methods mathscidoc:1712.33001

journal
[ Download ] [ 2017-12-10 10:19:33 uploaded by malidong ] [ 214 downloads ] [ 0 comments ] [ Abstract ] [ Full ]
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