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On the Use of Data Noise as a Site-Specific Weight Parameter in a Hierarchical Bayesian Moment Tensor Inversion: The Case Study of The Geysers and Long Valley Caldera Earthquakes

Mustać, Marija; Tkalčić, Hrvoje


We expand a method for seismic moment tensor inversion using probabilistic Bayesian inference, which yields parameter uncertainties and includes a thorough treatment of noise in the data, to include additional noise parameters that weight the contributions of particular stations. In a synthetic test, we show that having individual noise parameters for each station gives an optimal fit to the data. The noise determines the level of data fit at each station and in turn weights their contribution...[Show more]

CollectionsANU Research Publications
Date published: 2017
Type: Journal article
Source: Bulletin of the Seismological Society of America
DOI: 10.1785/0120160379


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