Shu-rong Zheng

Statistics and Probability · 2009–2019

A researcher in the Science corpus: 6 papers; trusts 42 researchers and is trusted by 15 researchers here, as inferred from the citation graph.

Subfields

• Statistics and Probability — 78 citations into it; #3,657 of 12,932 by trust here, #3,801 by citations
• Mathematical Physics — 33 citations into it; #6,863 of 8,562 by trust here, #6,594 by citations
• Discrete Mathematics and Combinatorics — 26 citations into it
• Artificial Intelligence — 23 citations into it; #28,800 of 35,345 by trust here, #28,481 by citations
• Economics and Econometrics — 12 citations into it
• Applied Mathematics — 7 citations into it; #5,895 of 7,620 by trust here, #5,850 by citations
• Computational Theory and Mathematics — 7 citations into it; #5,128 of 12,182 by trust here, #5,465 by citations
• Finance — 7 citations into it

Whom Shu-rong Zheng trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Z. Bai
2. Muni S. Srivastava
3. Tommaso Cai
4. Cedric E. Ginestet
5. Zhengjun Zhang
6. Olivier Ledoit
7. J. Silverstein
8. Jun Yu Li
9. A. Onatski
10. Melanie Birke

Who trusts Shu-rong Zheng overall

1. Tommaso Cai
2. Jianfeng Yao
3. Zhao Ren
4. Edgar Dobriban
5. Zeng Li
6. Harrison H. Zhou
7. Damien Passemier

Papers from Shu-rong Zheng's perspective

Ordered by how strongly the researchers Shu-rong Zheng trusts endorse each paper. Same corpus, a different order for every researcher.

1. Some hypothesis tests for the covariance matrix when the dimension is large compared to the sample size
2. Determining the Number of Factors in Approximate Factor Models
3. Covariance regularization by thresholding
4. Regularized estimation of large covariance matrices
5. On the distribution of the largest eigenvalue in principal components analysis
6. Some Tests Concerning the Covariance Matrix in High Dimensional Data
7. Determining the Number of Factors from Empirical Distribution of Eigenvalues (Review of Economics and Statistics)
8. CLT for linear spectral statistics of large-dimensional sample covariance matrices
9. Corrections to LRT on large-dimensional covariance matrix by RMT
10. A HIGH DIMENSIONAL TWO SAMPLE SIGNIFICANCE TEST

Their papers

• Corrections to LRT on large-dimensional covariance matrix by RMT (2009) — 266 citations
• Estimating Number of Factors by Adjusted Eigenvalues Thresholding (2019) — 106 citations
• Substitution principle for CLT of linear spectral statistics of high-dimensional sample covariance matrices with applications to hypothesis testing (2014) — 97 citations
• Large Sample Covariance Matrices and High-Dimensional Data Analysis (2015) — 182 citations
• Testing the independence of sets of large-dimensional variables (2013) — 46 citations
• Generalized Measures of Correlation for Asymmetry, Nonlinearity, and Beyond (2012) — 72 citations