Nonstationary matrix covariances: compact support, long range dependence and quasi-arithmetic constructions
Nonstationary matrix covariances: compact support, long range dependence and quasi-arithmetic constructions
复制标题
非平稳矩阵协方差：紧凑支持、长程依赖和准算术构造
DOI：
10.1007/s00477-014-0867-6
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发表时间：
2014
影响因子：
4.2
通讯作者：
E. Porcu
中科院分区：
文献类型：
--
作者：
W. Kleiber;E. Porcu
多变量过程的灵活模型对于地球物理、环境、经济和健康科学中的数据集越来越重要。现代数据集涉及在大量时空位置观察到的众多变量，通常有数百万个数据点。我们建立了一套非平稳多变量过程的随机模型。该结构分为三个基本类别准算术，局部平稳协方差与紧支持，局部平稳协方差与可能的长期依赖。所有衍生的模型是非平稳的，我们通过仿真说明了选择的灵活性。
Flexible models for multivariate processes are increasingly important for datasets in the geophysical, environmental, economics and health sciences. Modern datasets involve numerous variables observed at large numbers of space–time locations, with millions of data points being common. We develop a suite of stochastic models for nonstationary multivariate processes. The constructions break into three basic categories—quasi-arithmetic, locally stationary covariances with compact support, and locally stationary covariances with possible long-range dependence. All derived models are nonstationary, and we illustrate the flexibility of select choices through simulation.