Ningning Xia
Shanghai University of Finance and Economics
13 Papers
47 Citations
Ningning Xia is an academic researcher from Shanghai University of Finance and Economics. The author has contributed to research in topics: Covariance matrix & Covariance. The author has an hindex of 5, co-authored 11 publications. Previous affiliations of Ningning Xia include Northeast Normal University & National University of Singapore.
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Papers
Convergence rates of eigenvector empirical spectral distribution of large dimensional sample covariance matrix
TL;DR: In this paper, the convergence rate of the eigenvector empirical spectral distribution (VESD) of covariance matrices was shown to be O(n − 1/2 ) for any fixed ε > 0.
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On the inference about the spectral distribution of high-dimensional covariance matrix based on high-frequency noisy observations
Ningning Xia,Xinghua Zheng +1 more
TL;DR: In this article, the spectral distribution of the population covariance matrix under high-frequency data with micro-structure noise is investigated, and the authors establish an asymptotic relationship that describes how the limiting spectral distribution depends on that of signal-plus-noise-type sample covariance matrices.
Functional CLT of eigenvectors for large sample covariance matrices
Ningning Xia,Ningning Xia,Zhidong Bai,Zhidong Bai +3 more
- 01 Feb 2015
TL;DR: In this article, the central limit theorem of linear spectral statistics associated with a new form of empirical spectral distribution was established based on eigenvectors and eigenvalues of sample covariance matrix.
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Convergence rates of eigenvector empirical spectral distribution of large dimensional sample covariance matrix
TL;DR: In this paper, the convergence rate of the eigenvector empirical spectral distribution (VESD) of covariance matrices was shown to be O(n −1/2 ) for any fixed ε > 0.
On the Inference about the Spectral Distribution of High-Dimensional Covariance Matrix Based on High-Frequency Noisy Observations
Ningning Xia,Xinghua Zheng +1 more
TL;DR: In this paper, the spectral distribution of ICV matrices of high-dimensional diffusion processes based on high-frequency data with micro-structure noise was investigated, and the authors established an asymptotic relationship that describes how the limiting spectral distribution depends on that of signal-plus-noise-type sample co-variance matrices.
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