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Activity Number: 511 - Statistical Applications in the Physical Sciences
Type: Contributed
Date/Time: Wednesday, July 31, 2019 : 10:30 AM to 12:20 PM
Sponsor: Section on Physical and Engineering Sciences
Abstract #306609 Presentation
Title: Estimating Regional Phase Amplitudes with Left Censored Data in the Middle East
Author(s): Haya Aldossary* and Scott H. Holan and Eric Sandovl and Hongjun Hui
Companies: University of Missouri and University of Missouri/U.S. Census Bureau and University of Missouri and University of Missouri
Keywords: Bayesian; Censored data; Seismology; Tomography
Abstract:

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.


Authors who are presenting talks have a * after their name.

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