A PRACTICAL APPROACH TO SPATIO-TEMPORAL ANALYSIS

被引:1
|
作者
Jiang, Huijing [1 ]
Schoergendorfer, Angela [1 ]
Hwang, Youngdeok [1 ]
Amemiya, Yasuo [1 ]
机构
[1] IBM Thomas J Watson Res Ctr, Yorktown Hts, NY 10598 USA
关键词
Empirical orthogonal function based prediction; goodness-of-fit test; monitoring network; nonparametric covariance matrix; spatio-temporal modeling; MODELS;
D O I
10.5705/ss.2013.262w
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
This paper introduces a spatio-temporal statistical analysis approach appropriate for monitoring or managing a physical system in which measurements are taken over dense time resolution but at sparse locations. The proposed approach is designed for implementation in an automated and efficient operation with manual intervention required only for scenario analysis. The method is based on a modeling framework for complex predictor-response and spatio-temporal relationships, and issues model-based prediction intervals. To accommodate varying practical situations, the method also includes an automated decision criterion for choosing between parametric and nonparametric spatial covariance models. The approach is illustrated using a data center thermal management problem.
引用
收藏
页码:369 / 384
页数:16
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