Grantee Research Project Results
2001 Progress Report: Hierarchical Statistical Analysis of Global and Regional Environmental Data
EPA Grant Number: R827257Title: Hierarchical Statistical Analysis of Global and Regional Environmental Data
Investigators: Cressie, Noel A.C. , Berliner, Mark , Wikle, Christopher K.
Current Investigators: Cressie, Noel A.C. , Berliner, Mark , Wilke, Christopher K.
Institution: The Ohio State University , University of Missouri - Columbia
Current Institution: The Ohio State University , University of Missouri - Kansas City
EPA Project Officer: Hahn, Intaek
Project Period: September 1, 1998 through August 31, 2001 (Extended to March 31, 2003)
Project Period Covered by this Report: September 1, 2000 through August 31, 2001
Project Amount: $325,000
RFA: Environmental Statistics (1998) RFA Text | Recipients Lists
Research Category: Environmental Statistics , Human Health , Aquatic Ecosystems
Objective:
The first objective is to implement hierarchical spatio-temporal statistical modeling of environmental phenomena (e.g., sea-surface temperatures, disease mortality/morbidity rates, remote-sensing data). The second objective is to find computationally efficient ways to statistically filter massive spatio-temporal data sets, such as those obtained from polar-orbiting satellites. The third objective is to investigate ways to link two or more spatio-temporal environmental processes, one being explanatory for the other (e.g., meteorology might be explanatory for wetland ecology).
Progress Summary:
Hierarchical models for environmental phenomena were developed in Cressie and Johannesson (2001), Royle and Wikle (2001), Wikle (2001), Aldworth and Cressie (2002), Gabrosek and Cressie (2002), Huang et al. (2002), Mugglin et al. (2002), and Wikle (2002). Computational speed-ups were specifically considered in Cressie and Johannesson (2001) and Huang et al. (2002). The linking methodology is being explored but no papers have been written at this time. The general idea is to link the El Niño/La Niña forecasting skill obtained in Berliner, Wikle, and Cressie (2000), Journal of Climate, with the ecological research presented in Royle and Wikle (2001) and Wikle (2000). Other papers presented below, but not mentioned in this section, refer to individual studies in the area of spatial environmental statistics.
Future Activities:
In the final year of the grant, the following two problems will be considered. The first involves adapting the multi-resolution Kalman filter to include a dynamic component. The second is concerned with a Bayesian model of explanatory links between space-time environmental processes, specifically the link between precipitation and duck breeding pairs in the Prairies region of the United States.
Journal Articles on this Report : 12 Displayed | Download in RIS Format
| Other project views: | All 103 publications | 29 publications in selected types | All 19 journal articles |
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Aldworth J, Cressie N. Prediction of nonlinear spatial functionals. Journal of Statistical Planning and Inference 2003;112(1-2):3-41. |
R827257 (2001) R827257 (Final) |
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Cressie N, Collins LB. Analysis of spatial point patterns using bundles of product density LISA functions. Journal of Agricultural, Biological, and Environmental Statistics 2001;6(1):118-135. |
R827257 (2001) |
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Cressie N, Pardo L, del Carmen Pardo M. Size and power considerations for testing loglinear models using ϕ-divergence test statistics. Statistica Sinica 2003;13(2):555-570. |
R827257 (2001) R827257 (Final) |
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Gabrosek J, Cressie N. The effect on attribute prediction of location uncertainty in spatial data. Geographical Analysis 2002;34(3):262-285. |
R827257 (2001) R827257 (Final) |
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Huang H-C, Cressie N, Gabrosek J. Fast, resolution-consistent spatial prediction of global processes from satellite data. Journal of Computational and Graphical Statistics 2002;11(1):63-88. |
R827257 (2001) R827257 (Final) |
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Kaiser MS, Cressie N, Lee J. Spatial mixture models based on exponential family conditional distributions. Statistica Sinica 2002, Volume: 12, Number: 2 (APR), Page: 449-474. |
R827257 (2001) |
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Lahiri SN, Lee Y, Cressie N. On asymptotic distribution and asymptotic efficiency of least squares estimators of spatial variogram parameters. Journal of Statistical Planning and Inference 2002;103(1-2):65-85. |
R827257 (1999) R827257 (2001) R827257 (Final) |
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Lee J, Kaiser MS, Cressie N. Multiway dependence in exponential family conditional distributions. Journal of Multivariate Analysis 2001;79(2):171-190. |
R827257 (2001) |
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Mugglin AS, Cressie N, Gemmell I. Hierarchical statistical modelling of influenza epidemic dynamics in space and time. Statistics in Medicine 2002;21(18):2703-2721. |
R827257 (2001) R827257 (Final) |
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Shen XT, Huang HC, Cressie N. Nonparametric hypothesis testing for a spatial signal Journal of the American Statistical Association 2002, Volume: 97, Number: 460 (DEC), Page: 1122-1140. |
R827257 (2001) |
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Wikle CK. A kernel-based spectral model for non-Gaussian spatio-temporal processes. Statistical Modelling 2002;2(4):299-314. |
R827257 (2001) R827257 (Final) |
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Wikle CK. Hierarchical Bayesian models for predicting the spread of ecological processes. Ecology 2003;84(6):1382-1394. |
R827257 (2001) R827257 (Final) |
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Supplemental Keywords:
ambient air, atmosphere, global climate, stratospheric ozone, precipitation, health effects, ecological effects, human health, Bayesian, biology, ecology, epidemiology, mathematics, modeling, climate models, satellite, remote sensing, agriculture., RFA, Economic, Social, & Behavioral Science Research Program, Scientific Discipline, Air, Ecosystem Protection/Environmental Exposure & Risk, Ecology, air toxics, Ecosystem/Assessment/Indicators, Mathematics, climate change, Ecological Effects - Environmental Exposure & Risk, Environmental Statistics, atmospheric, risk assessment, regional environmental data, remote sensing, EMAP, environmental monitoring, stratospheric ozone, Bayesian space-time model, global environmental data, mortality rates, satellite data, statistical models, climate models, global warming, hierarchical statistical analysis, statistical methods, EOSRelevant Websites:
http://www.stat.ohio-state.edu/~sses Exit
http://www.stat.ohio-state.edu/~sses/research_epa.html Exit
Progress and Final Reports:
Original AbstractThe perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Conclusions drawn by the principal investigators have not been reviewed by the Agency.