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LARGE SAMPLE BEHAVIOUR OF HIGH DIMENSIONAL AUTOCOVARIANCE MATRICES

机译:高维自变矩阵的大样本行为

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The existence of limiting spectral distribution (LSD) of (Gamma) over cap (u) + (Gamma) over cap (u)*, the symmetric sum of the sample autocovariance matrix (Gamma) over cap (u) of order u, is known when the observations are from an infinite dimensional vector linear process with appropriate (strong) assumptions on the coefficient matrices. Under significantly weaker conditions, we prove, in a unified way, that the LSD of any symmetric polynomial in these matrices such as (Gamma) over cap (u) + (Gamma) over cap (u)*, (Gamma) over cap (u)(Gamma) over cap (u)*, (Gamma) over cap (u)(Gamma) over cap (u)* + (Gamma) over cap (k)(Gamma) over cap (k)* exist. Our approach is through the more intuitive algebraic method of free probability in conjunction with the method of moments. Thus, we are able to provide a general description for the limits in terms of some freely independent variables. All the previous results follow as special cases. We suggest statistical uses of these LSD and related results in order determination and white noise testing.
机译:上限(u)上的(γ)+上限(u)上的(γ)*的极限光谱分布(LSD)的存在,即上限u上的样本自协方差矩阵(Gamma)的对称总和是当观测值来自于对系数矩阵有适当(强烈)假设的无限维矢量线性过程时,则为已知。在明显较弱的条件下,我们以统一的方式证明了这些矩阵中任何对称多项式的LSD,例如(u)超过(u)的gamma +(u)*超过(u)*的(gamma),(cap)超过(u)的(γ) u)(超过上限(u)*)的伽玛(g)超过上限(u)*(u)*的伽玛(+)超过上限(k)(k)的伽玛(k)*我们的方法是通过更直观的自由概率代数方法和矩量方法。因此,我们可以根据一些自由自变量来提供极限的一般描述。前面所有结果均为特殊情况。我们建议对这些LSD及其相关结果进行统计使用,以进行顺序确定和白噪声测试。

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