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

Publication date: Available online 8 August 2018Source: Statistics & Probability LettersAuthor(s): Kimberly F. Manago, Terri S. Hogue, Aaron Porter, Amanda S. HeringAbstractGroundwater 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.

Source: Statistics and Probability Letters - August 9, 2018 Category: Statistics Source Type: research