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Residuals between ground‐motion data and ground‐motion prediction equations (GMPEs) can be decomposed into terms representing earthquake source, path, and site effects. These terms can be cast in terms of repeatable (epistemic) residuals and the random (aleatory) components. Identifying the repeatable residuals leads to a GMPE with reduced uncertainty for a specific source, site, or path location, which in turn can yield a lower hazard level at small probabilities of exceedance. We illustrate a schematic framework for this residual partitioning with a dataset from the ANZA network, which straddles the central San Jacinto fault in southern California. The dataset consists of more than 3200 earthquakes and their peak ground accelerations (PGAs), recorded at close distances (). We construct a small‐magnitude GMPE for these PGA data, incorporating site conditions and geometrical …