The limits of the sample spiked eigenvalues for a high-dimensional generalized Fisher matrix and its applications.

@article{Jiang2019TheLO,
  title={The limits of the sample spiked eigenvalues for a high-dimensional generalized Fisher matrix and its applications.},
  author={Dandan Jiang and Jiang Hu and Zhiqiang Hou},
  journal={arXiv: Statistics Theory},
  year={2019}
}
INVARIANCE PRINCIPLE AND CLT FOR THE SPIKED EIGENVALUES OF LARGE-DIMENSIONAL FISHER MATRICES AND APPLICATIONS
This paper aims to derive asymptotical distributions of the spiked eigenvalues of the large-dimensional spiked Fisher matrices without Gaussian assumption and the restrictive assumptions on
Invariance principle and CLT for the spiked eigenvalues of large-dimensional Fisher matrices and applications
This paper aims to derive asymptotical distributions of the spiked eigenvalues of the large-dimensional spiked Fisher matrices without Gaussian assumption and the restrictive assumptions on
Spiked eigenvalues of noncentral Fisher matrix with applications
In this paper, we investigate the asymptotic behavior of spiked eigenvalues of the noncentral Fisher matrix defined by Fp = Cn(SN ) −1, where Cn is a noncentral sample covariance matrix defined by

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