Grantee Research Project Results
Publications Details for Grant Number R826887
Combining Environmental Data Using Hierarchical Bayesian Space-Time Models
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Reference Type | Reference Title | Journal | Author | Citation | Progress Report Year | Document Sources |
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Journal Article | Combining snow water equivalent data from multiple sources to estimate spatio-temporal trends and compare measurement systems. | JOURNAL OF AGRICULTURAL, BIOLOGICAL, AND ENVIRONMENTAL STATISTICS | Cowles MK, Zimmerman DL, Christ A, McGinnis DL | Cowles MK, Zimmerman DL, Christ A, McGinnis DL. Combining snow water equivalent data from multiple sources to estimate spatio-temporal trends and compare measurement systems. Journal of Agricultural, Biological, and Environmental Statistics 2002, Volume: 7, Number: 4 (DEC), Page: 536-557. |
R826887 (2000) |
not available |
Journal Article | A Bayesian geostatistical model for comparing environmental data | OURNAL OF AGRICULTURAL, BIOLOGICAL, AND ENVIRONMENTAL STATISTICS VOLUME | Cowles MK | Cowles MK. A Bayesian geostatistical model for comparing environmental data. ournal of Agricultural, Biological, and Environmental Statistics volume 2002;7:236 |
R826887 (2000) |
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Journal Article | MCMC sampler convergence rates for hierarchical normal linear models: A simulation approach. | STATISTICS AND COMPUTING | Cowles MK | Cowles MK. MCMC sampler convergence rates for hierarchical normal linear models: A simulation approach. Statistics and Computing 2002;12(4):377-389. |
R826887 (1999) R826887 (2000) |
not available |
Journal Article | Efficient model-fitting and model-comparison for high-dimensional Bayesian geostatistical models. | JOURNAL OF STATISTICAL PLANNING AND INFERENCE | Cowles MK | Cowles, MK. Efficient model-fitting and model-comparison for high-dimensional Bayesian geostatistical models. Journal of Statistical Planning and Inference 2003;112(1-2):221-239. |
R826887 (2000) |
not available |
Journal Article | Combining temporally correlated environmental data from two measurement systems. | JOURNAL OF AGRICULTURAL, BIOLOGICAL, AND ENVIRONMENTAL STATISTICS | Isaacson JD, Zimmerman DL | Isaacson JD, Zimmerman DL. Combining temporally correlated environmental data from two measurement systems. Journal of Agricultural, Biological, and Environmental Statistics 2000;5(4):398-416. |
R826887 (1999) R826887 (2000) |
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Journal Article | Complementary co-kriging: spatial prediction using data combined from several environmental monitoring networks | ENVIRONMETRICS | Zimmerman DL, Holland DM | Zimmerman DL, Holland DM. Complementary co-kriging: spatial prediction using data combined from several environmental monitoring networks. Environmetrics 2005;16(3),219-234. |
R826887 (1999) |
not available |
Presentation | Assessing the proportion of treatment effect captured by two surrogate markers measured longitudinally | None | Cowles MK, Smith BJ | Cowles MK, Smith BJ. Assessing the proportion of treatment effect captured by two surrogate markers measured longitudinally. Presented to the Department of Biostatistics Colloquium, University of Iowa, November 2000. |
R826887 (2000) |
not available |
Presentation | MCMC convergence assessment | None | Cowles MK | Cowles MK. MCMC convergence assessment. Presented at the Eastern North American Region of the International Biometric Society Annual Meeting, Chicago, IL, March 2000. |
R826887 (2000) |
not available |
Presentation | MCMC sampler convergence rates for hierarchical normal linear models: a simulation approach | None | Cowles MK | Cowles MK. MCMC sampler convergence rates for hierarchical normal linear models: a simulation approach. Presented at the International Conference on Monte Carlo in the New Millennium, Gainesville, FL, January 2001. |
R826887 (2000) |
not available |
Presentation | Bayesian risk analysis of radon exposure data from the Iowa Radon Lung Cancer Study | None | Smith BJ, Cowles MK | Smith BJ, Cowles MK. Bayesian risk analysis of radon exposure data from the Iowa Radon Lung Cancer Study. Poster presented at the International Conference on Monte Carlo in the New Millennium, Gainesville, FL, January 2001. |
R826887 (2000) |
not available |
Presentation | Bayesian spatial analysis for data obtained from multiple measurement sources | None | Smith BJ, Cowles MK | Smith BJ, Cowles MK. Bayesian spatial analysis for data obtained from multiple measurement sources. Presented at the Eastern North America Region of the International Biometric Society Annual Meeting, Chicago, IL, March 2000. |
R826887 (2000) |
not available |
Presentation | Bayesian spatial analysis of radon exposure data from the Iowa Radon Lung Cancer Study | None | Smith BJ, Cowles MK | Bayesian spatial analysis of radon exposure data from the Iowa Radon Lung Cancer Study. Presented at the Joint Statistical Meetings, Indianapolis, IN, August 2000. |
R826887 (2000) |
not available |
Presentation | Bayesian spatial analysis of radon exposure data from the Iowa Radon Lung Cancer Study | None | Smith BJ, Cowles MK | Bayesian spatial analysis of radon exposure data from the Iowa Radon Lung Cancer Study. Presented at the Iowa Chapter of the American Statistical Association Annual Meeting, Indianola, IA, April 2000. |
R826887 (2000) |
not available |
Presentation | Modeling of environmental space-time data combined from multiple sources | None | Zimmerman DL | Zimmerman DL. Modeling of environmental space-time data combined from multiple sources. Presented at the Joint Statistical Meetings, Indianapolis, IN, August 2000. |
R826887 (2000) |
not available |
Presentation | Combining temporally and spatially correlated environmental data. | None | Zimmerman D | Zimmerman D. Combining temporally and spatially correlated environmental data. Presented at the National Institute of Statistical Science, 1999. |
R826887 (1999) |
not available |
The 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.