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Large Covariance Estimation by Thresholding Principal Orthogonal Complements

30 December 2011

Papers citing "Large Covariance Estimation by Thresholding Principal Orthogonal Complements"

50 / 142 papers shown

Title
Factor analysis in high dimensional biological data with dependent observations Chris McKennan CML 29 6 0 23 Sep 2020
Recent Developments on Factor Models and its Applications in Econometric Learning Jianqing Fan Kunpeng Li Yuan Liao 80 16 0 21 Sep 2020
Prediction in latent factor regression: Adaptive PCR and beyond Xin Bing F. Bunea Seth Strimas-Mackey M. Wegkamp 36 2 0 20 Jul 2020
Tensor Factor Model Estimation by Iterative Projection Yuefeng Han Rong Chen Dan Yang Cun-Hui Zhang AI4TS 81 29 0 04 Jun 2020
Beyond Data Samples: Aligning Differential Networks Estimation with Scientific Knowledge Arshdeep Sekhon Zhe Wang Yanjun Qi 35 0 0 24 Apr 2020
Doubly Debiased Lasso: High-Dimensional Inference under Hidden Confounding Zijian Guo Domagoj Cevid Peter Buhlmann CML 57 39 0 08 Apr 2020
Company classification using machine learning S. Husmann A. Shivarova R. Steinert 33 11 0 31 Mar 2020
Adaptive Estimation in Multivariate Response Regression with Hidden Variables Xin Bing Y. Ning Yaosheng Xu 55 4 0 30 Mar 2020
On Consistency and Sparsity for High-Dimensional Functional Time Series with Application to Autoregressions Shaojun Guo Xinghao Qiao AI4TS 42 11 0 23 Mar 2020
False Discovery Rate Control Under General Dependence By Symmetrized Data Aggregation Lilun Du Xu Guo Wenguang Sun Changliang Zou 40 44 0 27 Feb 2020
Hypothesis testing for eigenspaces of covariance matrix I. Silin Jianqing Fan 29 7 0 23 Feb 2020
Interpolating Predictors in High-Dimensional Factor Regression F. Bunea Seth Strimas-Mackey M. Wegkamp 65 12 0 06 Feb 2020
Bridging Convex and Nonconvex Optimization in Robust PCA: Noise, Outliers, and Missing Data Yuxin Chen Jianqing Fan Cong Ma Yuling Yan 86 52 0 15 Jan 2020
Statistical Inference for High-Dimensional Matrix-Variate Factor Model Elynn Y. Chen Jianqing Fan 109 66 0 07 Jan 2020
CDPA: Common and Distinctive Pattern Analysis between High-dimensional Datasets Hai Shu Zhe Qu 18 1 0 20 Dec 2019
Integrative Factor Regression and Its Inference for Multimodal Data Analysis Quefeng Li Lexin Li 80 27 0 11 Nov 2019
Ridge-type Linear Shrinkage Estimation of the Matrix Mean of High-dimensional Normal Distribution Ryota Yuasa T. Kubokawa 25 0 0 26 Oct 2019
SIMPLE: Statistical Inference on Membership Profiles in Large Networks Jianqing Fan Yingying Fan Xiao Han Jinchi Lv 67 43 0 03 Oct 2019
Optimal estimation of functionals of high-dimensional mean and covariance matrix Jianqing Fan Haolei Weng Yifeng Zhou 54 7 0 20 Aug 2019
Model-free Feature Screening and FDR Control with Knockoff Features Wanjun Liu Y. Ke Jingyuan Liu Runze Li 49 59 0 19 Aug 2019
Extending the Davis-Kahan theorem for comparing eigenvectors of two symmetric matrices II: Computation and Applications J. Lutzeyer S. M. I. A. T. Walden 25 0 0 09 Aug 2019
Extending the Davis-Kahan theorem for comparing eigenvectors of two symmetric matrices I: Theory J. Lutzeyer S. M. I. A. T. Walden 22 1 0 09 Aug 2019
Learning Latent Factors from Diversified Projections and its Applications to Over-Estimated and Weak Factors Jianqing Fan Yuan Liao 38 24 0 04 Aug 2019
High-dimensional principal component analysis with heterogeneous missingness Ziwei Zhu Tengyao Wang R. Samworth 183 50 0 28 Jun 2019
Estimation of the Kronecker Covariance Model by Quadratic Form O. Linton Haihan Tang 23 2 0 21 Jun 2019
Sparse Approximate Factor Estimation for High-Dimensional Covariance Matrices M. Daniele W. Pohlmeier A. Zagidullina 75 8 0 13 Jun 2019
Diagonally-Dominant Principal Component Analysis Z. Ke Lingzhou Xue Fan Yang 84 4 0 31 May 2019
Factor Models for High-Dimensional Functional Time Series Shahin Tavakoli Gilles Nisol Marc Hallin AI4TS 37 2 0 24 May 2019
Generalized Four Moment Theorem with an application to the CLT for the spiked eigenvalues of high-dimensional general Fisher-matrices Dandan Jiang Zhiqiang Hou Z. Bai 48 1 0 11 Apr 2019
Bayesian Factor-adjusted Sparse Regression Jianqing Fan Bai Jiang Qiang Sun 82 5 0 23 Mar 2019
Noisy Matrix Completion: Understanding Statistical Guarantees for Convex Relaxation via Nonconvex Optimization Yuxin Chen Yuejie Chi Jianqing Fan Cong Ma Yuling Yan 89 128 0 20 Feb 2019
Inference for Heterogeneous Effects using Low-Rank Estimation of Factor Slopes Victor Chernozhukov Christian B. Hansen Yuan Liao Yinchu Zhu 76 24 0 19 Dec 2018
User-Friendly Covariance Estimation for Heavy-Tailed Distributions Y. Ke Stanislav Minsker Zhao Ren Qiang Sun Wen-Xin Zhou 91 57 0 05 Nov 2018
RSVP-graphs: Fast High-dimensional Covariance Matrix Estimation under Latent Confounding Rajen Dinesh Shah Benjamin Frot Gian-Andrea Thanei N. Meinshausen 54 6 0 02 Nov 2018
Optimal Covariance Estimation for Condition Number Loss in the Spiked Model D. Donoho Behrooz Ghorbani 133 7 0 17 Oct 2018
Bayesian Estimation of Sparse Spiked Covariance Matrices in High Dimensions Fangzheng Xie Yanxun Xu Carey E. Priebe Joshua Cape 44 8 0 22 Aug 2018
Generalized Four Moment Theorem and an Application to CLT for Spiked Eigenvalues of Large-dimensional Covariance Matrices Dandan Jiang Z. Bai 26 30 0 16 Aug 2018
Robust high dimensional factor models with applications to statistical machine learning Jianqing Fan Kaizheng Wang Yiqiao Zhong Ziwei Zhu 86 55 0 12 Aug 2018
Optimal Subspace Estimation Using Overidentifying Vectors via Generalized Method of Moments Jianqing Fan Yiqiao Zhong 21 10 0 08 May 2018
Matrices with Gaussian noise: optimal estimates for singular subspace perturbation Sean O’Rourke Van Vu Ke Wang 72 7 0 02 Mar 2018
Testability of high-dimensional linear models with non-sparse structures Jelena Bradic Jianqing Fan Yinchu Zhu 53 16 0 26 Feb 2018
Hoeffding's lemma for Markov Chains and its applications to statistical learning Jianqing Fan Bai Jiang Qiang Sun 61 28 0 01 Feb 2018
On Variable Ordination of Modified Cholesky Decomposition for Sparse Covariance Matrix Estimation Xiaoning Kang Xinwei Deng 27 0 0 01 Jan 2018
The Dispersion Bias L. Goldberg A. Papanicolaou Alexander D. Shkolnik 58 16 0 15 Nov 2017
Limiting Laws for Divergent Spiked Eigenvalues and Largest Non-spiked Eigenvalue of Sample Covariance Matrices Tony Cai Xiao Han G. Pan 66 80 0 01 Nov 2017
Sparse covariance matrix estimation in high-dimensional deconvolution Denis Belomestny Mathias Trabs Alexandre B. Tsybakov 65 10 0 30 Oct 2017
Nonsparse learning with latent variables Zemin Zheng Jinchi Lv Wei Lin CML 34 1 0 07 Oct 2017
Adjusting systematic bias in high dimensional principal component scores Sungkyu Jung 25 5 0 16 Aug 2017
The two-to-infinity norm and singular subspace geometry with applications to high-dimensional statistics Joshua Cape M. Tang Carey E. Priebe 81 136 0 30 May 2017
On spectral properties of high-dimensional spatial-sign covariance matrices in elliptical distributions with applications Weiming Li Wang Zhou 11 1 0 18 May 2017