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 š _p=š_n(š_N)^-1, where š_n is a noncentral sample covariance matrix defined by (Ī+š)(Ī+š)^*/n and š_N=šš^*/N. The matrices š and š are two independent Gaussian arrays, with respective pĆ n and pĆ N and the Gaussian entries of them are independent and identically distributed (i.i.d.) with mean 0 and variance 1. When p, n, and N grow to infinity proportionally, we establish a phase transition of the spiked eigenvalues of š _p. Furthermore, we derive the central limiting theorem (CLT) for the spiked eigenvalues of š _p. As an accessory to the proof of the above results, the fluctuations of the spiked eigenvalues of š_n are studied, which should have its own interests. Besides, we develop the limits and CLT for the sample canonical correlation coefficients by the results of the spiked noncentral Fisher matrix and give three consistent estimators, including the population spiked eigenvalues and the population canonical correlation coefficients.
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