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arxiv: 1310.5428 · v1 · pith:UV5FF53Fnew · submitted 2013-10-21 · 🧮 math.PR

Convergence of Empirical Spectral Distributions of Large Dimensional Quaternion Sample Covariance Matrices

classification 🧮 math.PR
keywords quaternionmathbfcovarianceempiricalinftysamplespectraldistribution
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In this paper we establish the limit of the empirical spectral distribution of quaternion sample covariance matrices. Suppose $\mathbf X_n = ({x_{jk}^{(n)}})_{p\times n}$ is a quaternion random matrix. For each $n$, the entries $\{x_{ij}^{(n)}\}$ are independent random quaternion variables with a common mean $\mu$ and variance $\sigma^2>0$. It is shown that the empirical spectral distribution of the quaternion sample covariance matrix $\mathbf S_n=n^{-1}\mathbf X_n\mathbf X_n^*$ converges to the M-P law as $p\to\infty$, $n\to\infty$ and $p/n\to y\in(0,+\infty)$.

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