Articles | Volume 11, issue 7
https://doi.org/10.5194/gmd-11-3071-2018
https://doi.org/10.5194/gmd-11-3071-2018
Methods for assessment of models
 | 
31 Jul 2018
Methods for assessment of models |  | 31 Jul 2018

Bayesian inference of earthquake rupture models using polynomial chaos expansion

Hugo Cruz-Jiménez, Guotu Li, Paul Martin Mai, Ibrahim Hoteit, and Omar M. Knio

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Interactive discussion

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AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision
AR by Guotu Li on behalf of the Authors (13 Jun 2018)  Author's response    Manuscript
ED: Referee Nomination & Report Request started (15 Jun 2018) by Thomas Poulet
RR by Anonymous Referee #2 (21 Jun 2018)
RR by Anonymous Referee #1 (26 Jun 2018)
ED: Publish as is (30 Jun 2018) by Thomas Poulet
AR by Guotu Li on behalf of the Authors (08 Jul 2018)  Author's response    Manuscript
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Short summary
One of the most important challenges seismologists and earthquake engineers face is reliably estimating ground motion in an area prone to large damaging earthquakes. This study aimed at better understanding the relationship between characteristics of geological faults (e.g., hypocenter location, rupture size/location, etc.) and resulting ground motion, via statistical analysis of a rupture simulation model. This study provides important insight on ground-motion responses to geological faults.