title: Time-space Kriging to address the spatiotemporal misalignment in the large datasets.
abstract: This paper presents a Bayesian hierarchical spatiotemporal method of interpolation, termed as Markov Cube Kriging (MCK). The classical Kriging methods become computationally prohibitive, especially for large datasets due to the O(n3) matrix decomposition. MCK offers novel and computationally efficient solutions to address spatiotemporal misalignment, mismatch in the spatiotemporal scales and missing values across space and time in large spatiotemporal datasets. MCK is flexible in that it allows for non-separable spatiotemporal structure and nonstationary covariance at the hierarchical spatiotemporal scales. Employing MCK we developed estimates of daily concentration of fine particulates matter ≤2.5 μm in aerodynamic diameter (PM2.5) at 2.5 km spatial grid for the Cleveland Metropolitan Statistical Area, 2000 to 2009. Our validation and cross-validation suggest that MCK achieved robust prediction of spatiotemporal random effects and underlying hierarchical and nonstationary spatiotemporal structure in air pollution data. MCK has important implications for environmental epidemiology and environmental sciences for exposure quantification and collocation of data from different sources, available at different spatiotemporal scales.
authors.affiliation: Department of Epidemiology, University of Iowa, Iowa City, IA 52242, USA.
authors.forename: Dong
authors.initials: D
authors.lastname: Liang
authors.forename: Naresh
authors.initials: N
authors.lastname: Kumar
keywords: Bayesian computation; Fine particulate matter PM2.5; Gaussian Markov Random Fields; Nonstationarity; Spatiotemporal hierarchical model; Time-space Kriging
references.citation: J Am Stat Assoc. 2010 Jun 1;105(490):506-521
references.pmid: 20676229
references.citation: Biometrics. 2004 Dec;60(4):1034-42
references.pmid: 15606424
references.citation: J R Stat Soc Series B Stat Methodol. 2008 Sep 1;70(4):825-848
references.pmid: 19750209
references.citation: Aerosol Sci Technol. 2011 Sep;45(9):1090-1108
references.pmid: 22238503
references.citation: Atmos Environ (1994). 2007 Jul 1;41(21):4492-4503
references.pmid: 22180723
references.citation: Atmos Environ (1994). 2012 Mar 1;49:171-179
references.pmid: 22346563