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Activity Number: 509 - New Approaches to Modeling and Inference for Complex Space-Time Data
Type: Topic Contributed
Date/Time: Wednesday, August 1, 2018 : 10:30 AM to 12:20 PM
Sponsor: Section on Physical and Engineering Sciences
Abstract #330632 Presentation
Title: Identification of Management Zone Using a Spatial Clustering Time-Varying Lattice Models
Author(s): Youngdeok Hwang* and Huijing Jiang and Rodrigue Ngueyep
Companies: Sungkyunkwan University and IBM Research and IBM Research
Keywords: clustering; lattice model; lattice model; time-varying coefficients

When making a policy decision, it is important to identify the regions in which the policy would lead to a desirable outcome. When both covariates and responses are collected across geographical regions over time, such impacts are often spatially clustered and time-varying. We model this time-varying nature via a spatial lattice model with spatio-temporal varying coefficients. We propose a penalized likelihood method to incorporate the spatial structure while efficiently estimating the model parameters. We demostrate the merits of our method via simulation studies and a real life application.

Authors who are presenting talks have a * after their name.

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