Current ground-motion prediction equations invariably assume that site conditions at strong-motion stations, often characterized by the average shear-wave velocity to a depth of 30 m (VS30), are known to a uniform accuracy. This is, however, rarely the case. In this article, we present a regression procedure based on generalized least-squares and maximum-likelihood approaches that take into account the varying uncertainties on VS30. Assuming that VS30s for various groups of stations are known to different accuracies, application of this procedure to a large set of records from the Japanese KiK-net shows that the regression coefficients are largely insensitive to the assumption of nonuniform uncertainties. However, this procedure allows the computation of a site-specific standard deviation (σ) that should be used for sites where VS30 is known to different accuracies (e.g., a site only specified by class or a site with a measured VS profile). For sites with a measured VS profile, this leads to lower site-specific σ than for a site that is poorly characterized because this technique explicitly models the separation between the epistemic uncertainty in VS30 and the aleatory variability in predicted ground motion.

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