Activity Number:
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511
- Statistical Applications in the Physical Sciences
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Type:
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Contributed
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Date/Time:
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Wednesday, July 31, 2019 : 10:30 AM to 12:20 PM
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Sponsor:
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Section on Physical and Engineering Sciences
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Abstract #306609
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Presentation
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Title:
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Estimating Regional Phase Amplitudes with Left Censored Data in the Middle East
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Author(s):
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Haya Aldossary* and Scott H. Holan and Eric Sandovl and Hongjun Hui
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Companies:
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University of Missouri and University of Missouri/U.S. Census Bureau and University of Missouri and University of Missouri
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Keywords:
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Bayesian;
Censored data;
Seismology;
Tomography
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Abstract:
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One of the unique problems with predicting high frequency seismic wave amplitudes is the occurrence of wide spread phase blockage in the regional phase Sn. Sn is a shear wave which propagates horizontally through top of the Earth’s mantle. Sn is often systematically blocked in tectonically active regions, such as the Middle East. This blockage results in a left censored dataset, as blocked amplitudes fall below a limit of detection. Ignoring the censored data is problematic and can lead to biased predictions of the Sn amplitude. To correct the attenuation or Q models for systematic phase blockage, we propose a Bayesian regression model that incorporates the left-censored data by utilizing dependence in the wave paths and covariates. As a by-product of our approach we also provide measures of uncertainty. We illustrate our approach through simulation and prediction of Sn amplitudes in the Middle East.
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Authors who are presenting talks have a * after their name.