Baxter's inequality and convergence of finite predictors of multivariate stochastic processess
Baxter's inequality and convergence of finite predictors of multivariate stochastic processess
复制标题
巴克斯特不等式和多元随机过程有限预测变量的收敛性
DOI：
10.1007/bf01197341
复制
发表时间：
1993
影响因子：
2
通讯作者：
M. Pourahmadi
中科院分区：
文献类型：
--
作者：
R. Cheng;M. Pourahmadi
当密度满足有界性条件时，谱密度矩阵的光滑性与其最优因子密切相关。这对于证明Baxter不等式的多元推广和获得有限预报器的收敛速度是至关重要的。我们依赖于Lowdenlager和Rosenblum的技术，通过Toeplitz算子将最佳因子与谱密度联系起来。
SummaryWe show that smoothness properties of a spectral density matrix and its optimal factor are closely related when the density satisfies theboundedness condition. This is crucial in proving multivariate generalizations of Baxter's inequality and obtaining rates of convergence of finite predictors. We rely on a technique of Lowdenslager and Rosenblum relating the optimal factor to the spectral density via Toeplitz operators.