A Bayesian hierarchical model for multiple imputation of urban spatio-temporal groundwater levels

Kimberly F. Manago, Terri S. Hogue, Aaron Porter and Amanda S. Hering

Statistics & Probability Letters, 2019, vol. 144, issue C, 44-51

Abstract: Groundwater levels in urban areas are irregularly sampled and not well understood. Using a separable space–time Bayesian Hierarchical Model, we obtain multiple imputations of the missing values to analyze spatial and temporal groundwater level fluctuations in Los Angeles, CA.

Keywords: Bayesian hierarchical model; Multiple imputation; Separable space–time (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (1)

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DOI: 10.1016/j.spl.2018.07.023

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