Limiting spectral distribution of large-dimensional sample covariance matrices generated by VARMA
Limiting spectral distribution of large-dimensional sample covariance matrices generated by VARMA
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DOI：
10.1016/j.jmva.2009.06.011
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发表时间：
2009-10
期刊：
影响因子：
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通讯作者：
B. Jin;Cheng Wang;B. Miao;Mong-Na Lo Huang
中科院分区：
文献类型：
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作者：
B. Jin;Cheng Wang;B. Miao;Mong-Na Lo Huang
建立了由向量自回归移动平均（VARMA）模型生成的高维样本协方差矩阵存在极限谱分布（LSD）。特别地，我们得到了由一阶向量自回归（VAR(1)）模型和一阶向量移动平均（VMA(1)）模型生成的随机矩阵的lsd的显式形式，以及VAR(1)和VMA(1)的随机系数。对这些显式形式的参数也进行了估计。最后通过仿真验证了该方法的有效性。
The existence of a limiting spectral distribution (LSD) for a large-dimensional sample covariance matrix generated by the vector autoregressive moving average (VARMA) model is established. In particular, we obtain explicit forms of the LSDs for random matrices generated by a first-order vector autoregressive (VAR(1)) model and a first-order vector moving average (VMA(1)) model, as well as random coefficients for VAR(1) and VMA(1). The parameters for these explicit forms are also estimated. Finally, simulations demonstrate that the results are effective.