Applications on linear spectral statistics of high-dimensional sample covariance matrix with divergent spectrum

Yangchun Zhang, Yirui Zhou, Xiaowei Liu

Type: Article

Publication Date: 2022-09-13

Citations: 0

DOI: https://doi.org/10.1016/j.csda.2022.107617

View Publication

Locations

Computational Statistics & Data Analysis - View

Similar Works

Action	Title	Year	Authors
+	The convergence on spectrum of sample covariance matrices for information-plus-noise type data	2012	Junshan Xie
+	Spectra of infinite-dimensional sample covariance matrices	2006	V. Serdobolskii
+	Spectrum of High-Dimensional Sample Covariance and Related Matrices: A Selective Review	2024	Monika Bhattacharjee Arup Bose
+	Limiting spectral distribution of normalized sample covariance matrices with	2012	Junshan Xie
+	Limiting spectral distribution for a type of sample covariance matrices	2013	Junshan Xie
+	Large sample correlation matrices with unbounded spectrum	2024	Yanpeng Li
+	Asymptotic behavior of spectral function of empirical covariance matrices	1994	Vyacheslav L. Girko A. K. Gupta
+	Spectral analysis of normalized sample covariance matrices with large dimension and small sample size	2013	Binbin Chen
+ PDF Chat	Limiting Spectral Distribution of High-dimensional Hayashi-Yoshida Estimator of Integrated Covariance Matrix	2024	Rituparna Sen Arnab Chakrabarti
+ PDF Chat	On asymptotic expansion and CLT of linear eigenvalue statistics for sample covariance matrices when $N/M\rightarrow0$	2014	Zhigang Bao Zhigang Bao
+	Fluctuations for linear spectral statistics of large random covariance matrices	2014	Jamal Najım Jianfeng Yao
+	Central Limit Theory for Linear Spectral Statistics of Normalized Separable Sample Covariance Matrix	2021	Long Yu Jiahui Xie Zhou Wang
+	Extreme eigenvalues of sample covariance and correlation matrices	2017	Johannes Heiny
+	Resolvents and Spectral Functions of Large Sample Covariance Matrices	2000	V. Serdobolskii
+	Analysis of the limiting spectral distribution of large dimensional information-plus-noise type matrices	2007	R. Brent Dozier Jack W. Silverstein
+	Limiting spectral distribution of high-dimensional noncentral Fisher matrices and its analysis	2022	Xiaozhuo Zhang Zhidong Bai Jiang Hu
+	Asymptotic normality of spectral estimates	1985	Rainer Dahlhaus
+	Spectral statistics of high dimensional sample covariance matrix with unbounded population spectral norm	2021	Yanqing Yin
+ PDF Chat	Spectral statistics of high dimensional sample covariance matrix with unbounded population spectral norm	2022	Yanqing Yin
+	General tool for estimating effects of unknown correlations on spectral integrals	2019	Tomi Pulli Anna Vaskuri Petri Kärhä Henrik Mäntynen Erkki Ikonen

Works That Cite This (0)

Action	Title	Year	Authors

Works Cited by This (23)

Action	Title	Year	Authors
+ PDF Chat	On the distribution of the largest eigenvalue in principal components analysis	2001	Iain M. Johnstone
+ PDF Chat	Estimation of the population spectral distribution from a large dimensional sample covariance matrix	2013	Weiming Li Jiaqi Chen Yingli Qin Zhidong Bai Jianfeng Yao
+ PDF Chat	CLT for linear spectral statistics of large-dimensional sample covariance matrices	2004	Zhidong Bai Jack W. Silverstein
+ PDF Chat	A local moment estimator of the spectrum of a large dimensional covariance matrix	2013	Weiming Li Jianfeng Yao
+	Substitution principle for CLT of linear spectral statistics of high-dimensional sample covariance matrices with applications to hypothesis testing	2015	Shurong Zheng Zhidong Bai Jianfeng Yao
+ PDF Chat	Some Tests Concerning the Covariance Matrix in High Dimensional Data	2005	Muni S. Srivastava
+	Improved Estimation of Eigenvalues and Eigenvectors of Covariance Matrices Using Their Sample Estimates	2008	Xavier Mestre
+	ESTIMATION OF SPIKED EIGENVALUES IN SPIKED MODELS	2012	Zhidong Bai Xue Ding
+ PDF Chat	On Estimation of the Noise Variance in High Dimensional Probabilistic Principal Component Analysis	2015	Damien Passemier Zhaoyuan Li Jianfeng Yao
+	Multivariate sign-based high-dimensional tests for sphericity	2013	Changliang Zou Liuhua Peng Long Feng Zhaojun Wang