Ground motion spatial correlation fitting methods and estimation uncertainty |
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Authors: | Jack W. Baker Yilin Chen |
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Affiliation: | Department of Civil and Environmental Engineering, Stanford University, Stanford, California, USA |
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Abstract: | Ground shaking intensity varies spatially in earthquakes, and many studies have estimated correlations of intensity from past earthquake data. This paper presents a framework for quantifying uncertainty in the estimation of correlations and true variability in correlations from earthquake to earthquake. A procedure for evaluating estimation uncertainty is proposed and used to evaluate several methods that have been used in past studies to estimate correlations. The results indicate that a weighted least squares algorithm is most effective in estimating spatial correlation models and that earthquakes with at least 100 recordings are needed to produce informative earthquake-specific estimates of spatial correlations. The proposed procedure is also used to distinguish between estimation uncertainty and the true variability in model parameters that exist in a given data set. The estimation uncertainty is seen to vary between well-recorded and poorly recorded earthquakes, whereas the true variability is more stable. |
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Keywords: | event-to-event variability infrastructure systems spatial correlation spectral accelerations |
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