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Activity Number:
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80
- Advancement in Spatial and Spatiotemporal Point Process
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Type:
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Contributed
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Date/Time:
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Sunday, July 29, 2018 : 4:00 PM to 5:50 PM
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Sponsor:
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Section on Statistics and the Environment
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Abstract #328965
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Presentation
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Title:
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Inferring Spatial Point Intensity of Geomagnetic Anomalies from Transect Sampling
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Author(s):
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Kenneth Flagg* and Andrew Hoegh and Megan Higgs and John Borkowski
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Companies:
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Montana State University and Montana State University and Montana State University and Montana State University
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Keywords:
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Bayesian statistics;
spatial point process;
Dirichlet process;
unexploded ordnance
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Abstract:
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Geomagnetic anomalies recorded at munitions use sites are often collected along transects that cover a very small proportion of the site area. Munitions items are assumed to occur in elliptical regions of high point intensity, so a primary analysis goal is to map the intensity over the site and identify high-intensity regions that might contain unexploded ordnance. We propose a Bayesian spatial Poisson process model with a Dirichlet process mixture as the inhomogeneous intensity function. Then we incorporate data augmentation into a Gibbs sampler to fit the model to data observed in a subset of the site region. We demonstrate fitting the model to simulated data, using both the fully-observed region and the restriction to two different subsets. Finally, we fit the model to data collected at the Victorville Precision Bombing range in southern California.
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Authors who are presenting talks have a * after their name.
