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  1. Journal of Agricultural, Biological, and Environmental Statistics
  2. Journal of Agricultural, Biological, and Environmental Statistics : Volume 15
  3. Journal of Agricultural, Biological, and Environmental Statistics : Volume 15, Issue 2, June 2010
  4. Spatial Inference of Nitrate Concentrations in Groundwater
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Journal of Agricultural, Biological, and Environmental Statistics : Volume 22
Journal of Agricultural, Biological, and Environmental Statistics : Volume 21
Journal of Agricultural, Biological, and Environmental Statistics : Volume 20
Journal of Agricultural, Biological, and Environmental Statistics : Volume 19
Journal of Agricultural, Biological, and Environmental Statistics : Volume 18
Journal of Agricultural, Biological, and Environmental Statistics : Volume 17
Journal of Agricultural, Biological, and Environmental Statistics : Volume 16
Journal of Agricultural, Biological, and Environmental Statistics : Volume 15
Journal of Agricultural, Biological, and Environmental Statistics : Volume 15, Issue 4, December 2010
Journal of Agricultural, Biological, and Environmental Statistics : Volume 15, Issue 3, September 2010
Journal of Agricultural, Biological, and Environmental Statistics : Volume 15, Issue 2, June 2010
A Calibration Experiment in a Longitudinal Survey With Errors-in-Variables
Estimating the Risk of a Crop Epidemic From Coincident Spatio-temporal Processes
A Spatio-Temporal Downscaler for Output From Numerical Models
A Measurement Error Model for Heterogeneous Capture Probabilities in Mark-Recapture Experiments: An Estimating Equation Approach
Spatial Inference of Nitrate Concentrations in Groundwater
Improving Estimates of Abundance by Aggregating Sparse Capture-Recapture Data
Estimating Population Growth Rate From Capture–Recapture Data in Presence of Capture Heterogeneity
Predicting Life-History Traits for Female New Zealand Sea Lions, Phocarctos hookeri: Integrating Short-Term Mark-Recapture Data and Population Modeling
Journal of Agricultural, Biological, and Environmental Statistics : Volume 15, Issue 1, March 2010
Journal of Agricultural, Biological, and Environmental Statistics : Volume 14
Journal of Agricultural, Biological, and Environmental Statistics : Volume 13
Journal of Agricultural, Biological, and Environmental Statistics : Volume 12
Journal of Agricultural, Biological, and Environmental Statistics : Volume 11
Journal of Agricultural, Biological, and Environmental Statistics : Volume 10
Journal of Agricultural, Biological, and Environmental Statistics : Volume 9
Journal of Agricultural, Biological, and Environmental Statistics : Volume 8
Journal of Agricultural, Biological, and Environmental Statistics : Volume 7
Journal of Agricultural, Biological, and Environmental Statistics : Volume 6

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Spatial Inference of Nitrate Concentrations in Groundwater

Content Provider Springer Nature Link
Author Woodard, Dawn B. Wolpert, Robert L. O’Connell, Michael A.
Copyright Year 2009
Abstract We develop a method for multiscale estimation of pollutant concentrations, based on a nonparametric spatial statistical model. We apply this method to estimate nitrate concentrations in groundwater over the mid-Atlantic states, using measurements gathered during a period of 10 years. A map of the fine-scale estimated nitrate concentration is obtained, as well as maps of the estimated county-level average nitrate concentration and similar maps at the level of watersheds and other geographic regions. The fine-scale and coarse-scale estimates arise naturally from a single model, without refitting or ad hoc aggregation. As a result, the uncertainty associated with each estimate is available, without approximations relying on high spatial density of measurements or parametric distributional assumptions.Several risk measures are also obtained, including the probability of the pollutant concentration exceeding a particular threshold. These risk measures can be obtained at the fine scale, or at the level of counties or other regions.The nonparametric Bayesian statistical model allows for this flexibility in estimation while avoiding strong assumptions. This method can be applied directly to estimate ozone concentrations in air, pesticide concentrations in groundwater, or any other quantity that varies over a geographic region, based on approximate measurements at some locations and perhaps of associated covariates. An S-PLUS package with this capability is provided as supplemental material.
Starting Page 209
Ending Page 227
Page Count 19
File Format PDF
ISSN 10857117
Journal Journal of Agricultural, Biological, and Environmental Statistics
Volume Number 15
Issue Number 2
e-ISSN 15372693
Language English
Publisher Springer-Verlag
Publisher Date 2010-01-28
Publisher Place New York
Access Restriction One Nation One Subscription (ONOS)
Subject Keyword Bayesian Geostatistics Kriging Lévy processes Nonparametrics Response surface Spatial moving average Biostatistics Environmental Monitoring/Analysis Agriculture Statistics for Life Sciences, Medicine, Health Sciences
Content Type Text
Resource Type Article
Subject Applied Mathematics Statistics and Probability Environmental Science Agricultural and Biological Sciences Statistics, Probability and Uncertainty
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