A Spatiotemporal Model for Pollutant Concentrations |
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Authors: | Euikyoo Lee Myung-Sang Moon |
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Institution: | 1. Department of Applied Statistics , Konkuk University , Seoul, South Korea;2. Department of Information and Statistics , Yonsei University , Kangwondo, South Korea |
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Abstract: | ABSTRACT Contamination of underground water tables can be characterized by measurements that are mixtures of short-term spiking, long-term decline, and steady-state variations in contaminant levels. Classical statistical models often fail to capture the changes in contaminant flow because they rely on fitting smooth spatial and temporal functions across the region, smooth functions that might not comprehensively characterize contaminant change. In this article, a more comprehensive approach is presented for modeling such processes. This approach uses a new class of spatiotemporal models that can characterize a broad range of environmental processes. It also effectively uses Bayesian hierarchical model fitting and a novel use of near neighbors to model contamination in an underground water table. |
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Keywords: | ARIMA modeling Bayesian hierarchical fitting Near neighbors Semivariogram models |
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