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arXiv 1108.3147math.PR
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样本自协方差矩阵的极限谱分布

Limiting spectral distribution of sample autocovariance matrices

Anirban Basak, Arup Bose, Sanchayan Sen

摘要:

当时间序列是一个线性过程且对系数有合理的限制时,我们证明了样本自协方差矩阵(ACVM)的经验谱分布(ESD)随维数的增加而收敛.该限制不取决于基础驱动i.i.d.的分布。序列及其支持是无界的。该限度与理论ACVM的谱分布不一致。然而,如果我们考虑样本ACVM的适当锥形版本,则会出现这种情况。对于带状样本ACVM,只要与矩阵的维数成比例的非零对角线的数量有界远离零,则极限具有无界支持。如果该比值趋于零,则极限存在,并且再次与理论ACVM的谱分布一致。最后,我们还研究了非负定的ACVM的自然修改版本的LSD。

英文摘要:

We show that the empirical spectral distribution (ESD) of the sample autocovariance matrix (ACVM) converges as the dimension increases, when the time series is a linear process with reasonable restriction on the coefficients. The limit does not depend on the distribution of the underlying driving i.i.d. sequence and its support is unbounded. This limit does not coincide with the spectral distribution of the theoretical ACVM. However, it does so if we consider a suitably tapered version of the sample ACVM. For banded sample ACVM the limit has unbounded support as long as the number of non-zero diagonals in proportion to the dimension of the matrix is bounded away from zero. If this ratio tends to zero, then the limit exists and again coincides with the spectral distribution of the theoretical ACVM. Finally, we also study the LSD of a naturally modified version of the ACVM which is not non-negative definite.

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