Karhunen- Loeve Expansion for Massive Spatial Data

摘要：

Massive spatial data are observed in environmental studies and present a computational challenge to statistical analysis because of the large covariance matrix involved. The KL expansion is a useful tool for analyzing massive spatial data because it can reduce the model complexity. This article develops and compares two algorithms to obtain the eigenvalues and eigenfunctions in the Karhunen-Loeve expansion for spatial processes. The results can be used to make spatial interpolations given massive spatial data.

关键词： Covariance function Karhunen-Loeve expansion remove sensing spatial massive data

作者: Juan Hu Hao Zhang

作者单位: Department of Statistics Purdue University West Lafayette, IN 47907 USA Institute of Statistics and Decisions University of International Business and Economics Beijing 100

会议类型: 国际会议

会议名称: 2012 International Conference on Future Communication and Computer Technology(2012未来通信与计算机技术国际会议ICFCCT 2012)

会议地点: 哈尔滨

会议语种:英文

页码: 153-161

在线出版日期: 2012-05-19（万方平台首次上网日期，不代表论文的发表时间）