Statistics Theory and Methods

[1] Rerandomization Strategies for Balancing Covariates Using Pre-Experimental Longitudinal Data

Per Johansson Uppsala University and IFAU, Uppsala, Sweden; Tsinghua University, Beijing, China Mårten Schultzberg Uppsala University, Uppsala, Sweden

Statistics Theory and Methods mathscidoc:2206.33005

Journal of Computational and Graphical Statistics, 29, (4), 798-813, 2020.5
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[2] Asymptotic Inference for Optimal Rerandomization Designs

Mårten Schultzberg Uppsala University, Sweden Per Johansson Uppsala University, Sweden; Tsinghua University, China

Statistics Theory and Methods mathscidoc:2206.33004

Open Statistics, 1, (1), 49-58, 2021.1
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[3] On optimal rerandomization designs

Per Johansson Uppsala University and IFAU, Uppsala, Sweden; Tsinghua University, Beijing, China Donald B. Rubin Tsinghua University, Beijing, China Mårten Schultzberg Uppsala University, Uppsala, Sweden

Statistics Theory and Methods mathscidoc:2206.33003

Journal of the Royal Statistical Society: Series B (Statistical Methodology), 83, (2), 395-403, 2021.4
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[4] Plug-in L2-upper error bounds in deconvolution, for a mixing density estimate in Rd and for its derivatives, via the L1-error for the mixture

Yannis G. Yatracos Yau Mathematical Sciences Center, Tsinghua University, Beijing, People's Republic of China; School of Communication and Media Studies, Cyprus University of Technology, Lemesos, Cyprus

Statistics Theory and Methods mathscidoc:2206.33002

Statistics, 53, (6), 1251-1268, 2019.7
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[5] Inference in Experiments Conditional on Observed Imbalances in Covariates

Per Johansson Department of Statistics, Uppsala University, Uppsala, Sweden; IFAU, Uppsala, Sweden; Tsinghua University, Beijing, China Mattias Nordin Department of Statistics, UCFS and Urban Lab, Uppsala University, Uppsala, Sweden

Statistics Theory and Methods mathscidoc:2206.33001

The American Statistician, 00, (0), 1-11, 2022.4
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[6] On definitive screening designs using Paley’s conference matrices

Yaping Wang KLATASDS–MOE, School of Statistics, East China Normal University, Shanghai 200062, China Sixu Liu Yau Mathematical Sciences Center, Tsinghua University, Beijing 100084, China Dennis K.J. Lin Department of Statistics, Purdue University, West Lafayette, IN 47907, USA

Statistics Theory and Methods mathscidoc:2204.33001

Statistics & Probability Letters, 181, 109267, 2022.2
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[7] Edge statistics of large dimensional deformed rectangular matrices

Xiucai Ding University of California, Davis Fan Yang University of Pennsylvania

Probability Statistics Theory and Methods mathscidoc:2111.28002

2021.11
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[8] Tracy-Widom distribution for the edge eigenvalues of Gram type random matrices

Xiucai Ding University of California, Davis Fan Yang University of Pennsylvania

Probability Statistics Theory and Methods mathscidoc:2111.28001

2021.11
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[9] Limiting distribution of the sample canonical correlation coefficients of high-dimensional random vectors

Fan Yang fyang75@wharton.upenn.edu

Probability Statistics Theory and Methods mathscidoc:2110.28004

2021.10
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[10] Sample canonical correlation coefficients of high-dimensional random vectors with finite rank correlations

Zongming Ma University of Pennsylvania Fan Yang University of Pennsylvania

Probability Statistics Theory and Methods mathscidoc:2110.28003

2021.10
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[11] ComNet: Combinational Neural Network for Object Detection in UAV-Borne Thermal Images

Minglei Li Xingke Zhao Jiasong Li Liangliang Nan

Information Theory Probability Statistics Theory and Methods Machine Learning Data Analysis Statistics Theory and Methods,Data Analysis mathscidoc:2106.19001

IEEE Transactions on Geoscience and Remote Sensing, 2020.10
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[12] Estimating sparse precision matrix: optimal rates of convergence and adaptive estimation

T. TONY CAI University of Pennsylvania WEIDONG LIU Shanghai Jiao Tong University HARRISON H. ZHOU Yale University

Statistics Theory and Methods mathscidoc:2105.33003

The Annals of Statics, 2016.6
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[13] Supplementary material to “Panning for gold: Model-X knock- offs for high-dimensional controlled variable selection”

Emmanuel Candes Stanford University Yingying Fan University of Southern California, Los Angeles Lucas Janson Stanford University Jinchi Lv University of Southern California, Los Angeles

Statistics Theory and Methods mathscidoc:2105.33002

Journal of the Royal Statistical Society Series B, 80, 2018.6
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[14] Panning for gold:‘model-X’ knockoffs for high dimensional controlled variable selection

Emmanuel Candes Stanford University Yingying Fan University of Southern California, Los Angeles Lucas Janson Stanford University Jinchi Lv University of Southern California, Los Angeles

Statistics Theory and Methods mathscidoc:2105.33001

Journal of the Royal Statistical Society Series B, 80, 2018.6
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[15] On model selection from a finite family of possibly misspecified time series models

Ching-Kang Ing National Tsing Hua University HOWELL TONG University of Electronic Science & Technology HSIANG-LING HSU National University of Kaohsiung

Statistics Theory and Methods mathscidoc:2103.33002

Annals of Statistics, 47, 2019.4
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[16] Model selection for high-dimensional linear regression with dependent observations

Ching-Kang Ing National Tsing Hua University

Statistics Theory and Methods mathscidoc:2103.33001

Annals of Statistics, 48, 2020.9
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[17] Rate-optimal perturbation bounds for singular subspaces with applications to high-dimensional statistics

T. Tony Cai University of Pennsylvania Anru Zhang University of Wisconsin-Madison

Statistics Theory and Methods mathscidoc:2008.33001

The Annals of Statistics, 46, 2018
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[18] Asymptotics For High Dimensional Regression M-Estimates: Fixed Design Results

Lihua Lei Stanford University Peter J. Bickel University of California, Berkeley Noureddine El Karoui University of California, Berkeley

Statistics Theory and Methods mathscidoc:2005.33003

Probability Theory and Related Fields, 172, 983–1079, 2018.12
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[19] Solving Random Quadratic Systems of Equations Is Nearly as Easy as Solving Linear Systems

Yuxin Chen Princeton University Emmanuel Candes Stanford University

Statistics Theory and Methods mathscidoc:2005.33002

Gold Award Paper in 2020

Communications on Pure and Applied Mathematics, 70, (5), 822- 883, 2017.5
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[20] Fast community detection by SCORE

Jiashun Jin Carnegie Mellon University

Statistics Theory and Methods mathscidoc:2005.33001

Distinguished Paper Award in 2020

Annals of Statistics , 43, (1), 57-89, 2015.2
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[21] G-sup: a clustering algorithm for cryo-electron microscopy images of asymmetric particles

Ting-Li Chen Institute of Statistical Science, Academia Sinica Dai-Ni Hsieh Institute of Statistical Science, Academia Sinica Hung Hung Institute of Epidemiology and Preventive Medicine I-Ping Tu Institute of Statistical Science, Academia Sinica Pei-Shien Wu Dept. of Biostatistics, Duke University Yi-Ming Wu Institute of Chemistry, Academia Sinica Wei-Hau Chang Institute of Chemistry, Academia Sinica Su-Yun Huang Institute of Statistical Science, Academia Sinica

Statistics Theory and Methods Data Analysis, Bio-Statistics, Bio-Mathematics mathscidoc:2004.33002

The Annals of Applied Statistics , 8, (1), 259-285, 2014
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[22] The Bivariate Lack-of-Memory Distributions

Gwo Dong Lin Academia Sinica Xiaoling Dou Waseda University Satoshi Kuriki The Institute of Statistical Mathematics

Statistics Theory and Methods mathscidoc:2004.33001

Sankhya A, 81, (2), 273-297, 2019.12
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[23] Propagation of singularities in the solutions to the Boltzmann equation near equilibrium

Renjun Duan Meng-Rong Li Tong Yang

Statistics Theory and Methods mathscidoc:1912.43958

Mathematical Models and Methods in Applied Sciences, 18, (7), 1093-1114, 2008.7
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[24] Diffusion in a continuum model of self-propelled particles with alignment interaction

Pierre Degond Tong Yang

Statistics Theory and Methods mathscidoc:1912.43945

Mathematical Models and Methods in Applied Sciences, 20, 1459-1490, 2010.9
[ Download ] [ 2019-12-24 21:08:25 uploaded by Tong_Yang ] [ 232 downloads ] [ 0 comments ] [ Abstract ] [ Full ]
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[25] Lecture 3: Fourth Order BSS Method

Jack Xin

Statistics Theory and Methods mathscidoc:1912.43924

[ Download ] [ 2019-12-24 21:07:04 uploaded by Jack_Xin ] [ 194 downloads ] [ 0 comments ] [ Abstract ] [ Full ]
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