Limiting spectral distribution of large dimensional Spearman’s rank correlation matrices

Zeyu Wu, Cheng Wang

Type: Article

Publication Date: 2022-05-20

Citations: 9

DOI: https://doi.org/10.1016/j.jmva.2022.105011

View Publication

Download PDF

Locations

Journal of Multivariate Analysis - View
arXiv (Cornell University) - View - PDF
DataCite API - View

Similar Works

Action	Title	Year	Authors
+	Limiting spectral distribution for large sample correlation matrices	2022	Nina Dörnemann Johannes Heiny
+	Central Limit Theorem for Linear Spectral Statistics of Large Dimensional Kendall's Rank Correlation Matrices and its Applications	2019	Zeng Li Qinwen Wang Runze Li
+ PDF Chat	On eigenvalues of a high dimensional Kendall's rank correlation matrix with dependences	2021	Cheng Wang Qinwen Wang Zeng Li
+ PDF Chat	Central limit theorem for linear spectral statistics of large dimensional Kendall’s rank correlation matrices and its applications	2021	Zeng Li Qinwen Wang Runze Li
+	The limiting spectral distribution of the sample canonical correlation matrix	2023	Xiaozhuo Zhang
+ PDF Chat	Large dimensional Spearman's rank correlation matrices: The central limit theorem and its applications	2024	Hantao Chen Cheng Wang
+	Spectral statistics of large dimensional Spearman’s rank correlation matrix and its application	2015	Zhigang Bao Liang-Ching Lin Guangming Pan Wang Zhou
+	On eigenvalues of a high-dimensional Kendall's rank correlation matrix with dependence	2021	Zeng Li Cheng Wang Qinwen Wang
+ PDF Chat	Spectral properties of high dimensional rescaled sample correlation matrices	2024	Weijiang Chen Shurong Zheng Tingting Zou
+	Limiting spectral distribution of normalized sample covariance matrices with	2012	Junshan Xie
+	Spectral analysis of the Moore–Penrose inverse of a large dimensional sample covariance matrix	2016	Taras Bodnar Holger Dette Nestor Parolya
+	Sample Covariance Matrices and the Marčenko-Pastur Law	2009	Zhidong Bai Jack W. Silverstein
+	The Limiting Distribution of the Rank Correlation Coefficient $${R_g}$$	1989	Rudy A. Gideon Michael J. Prentice Ronald Pyke
+	Convergence rates of eigenvector empirical spectral distribution of large dimensional sample covariance matrix	2013	Ningning Xia Yingli Qin Zhidong Bai
+ PDF Chat	Necessary and sufficient condition for CLT of linear spectral statistics of sample correlation matrices	2024	Yanpeng Li Guangming Pan Jiahui Xie Wang Zhou
+	Marčenko-Pastur Law for Kendall's Tau	2016	Afonso S. Bandeira Asad Lodhia Philippe Rigollet
+	Marčenko-Pastur law for Kendall’s tau	2017	Afonso S. Bandeira Asad Lodhia Philippe Rigollet
+ PDF Chat	Limiting distribution of the sample canonical correlation coefficients of high-dimensional random vectors	2022	Fan Yang
+	On spectrum of sample covariance matrices from large tensor vectors	2023	Wangjun Yuan
+	Large sample correlation matrices with unbounded spectrum	2024	Yanpeng Li

Works That Cite This (1)

Action	Title	Year	Authors
+	Robust estimation for number of factors in high dimensional factor modeling via Spearman correlation matrix	2024	Jiaxin Qiu Zeng Li Jianfeng Yao

Works Cited by This (22)

Action	Title	Year	Authors
+ PDF Chat	Spectral Analysis of Large Dimensional Random Matrices	2009	Zhidong Bai Jack W. Silverstein
+	Robust Nonparametric Statistical Methods	2010	Thomas P. Hettmansperger Joseph W. McKean
+	A NEW MEASURE OF RANK CORRELATION	1938	M. G. Kendall
+	DISTRIBUTION OF EIGENVALUES FOR SOME SETS OF RANDOM MATRICES	1967	V A Marčenko L. А. Pastur
+	The Nonparanormal: Semiparametric Estimation of High Dimensional Undirected Graphs	2009	Han Liu John Lafferty Larry Wasserman
+	High-dimensional semiparametric Gaussian copula graphical models	2012	Han Liu Fang Han Ming Yuan John Lafferty Larry Wasserman
+ PDF Chat	An overview of the estimation of large covariance and precision matrices	2016	Jianqing Fan Yuan Liao Han Liu
+	LARGE SAMPLE COVARIANCE MATRICES WITHOUT INDEPENDENCE STRUCTURES IN COLUMNS	2008	Zhidong Bai Zhou Wang
+	The limiting distributions of eigenvalues of sample correlation matrices	2004	Tiefeng Jiang
+	Robust test for independence in high dimensions	2016	Guangyu Mao