Practical Approaches to Spatio-Temporal Analysis

• Activity Number: 164
• Type: Topic Contributed
• Date/Time: Monday, August 4, 2014 : 10:30 AM to 12:20 PM
• Sponsor: Quality and Productivity Section
• Author(s): Huijing Jiang*+ and Yasuo Amemiya
• Companies: IBM and IBM Research
• Keywords: spatio-temporal prediction ; continuous and count measurements ; nonparamatric spatial covariance matrix ; automated algorithm

Abstract

Many spatio-temporal analysis arising from business problems involve either continuous or count measurements taken at fixed locations but continuously come in over time. Under such circumstances, computational methods need to be expeditious for repeated model fitting and issuing predictions as new data arrives continuously, while being able to accommodate complex spatio-temporal relationships. To respond to this emerging need, we developed a flexible model fitting and forecast framework which can issue temporal forecasting and spatial prediction for both continuous or count measurements. The modeling and its computational algorithm are designed for automated and efficient operation with minimal manual intervention. External factors are incorporated as covariates in the model for system diagnosis and future scenario analysis. Industry applications will be presented to illustrate our approaches.