<p>A seismic hazard analysis was conducted for a site in Papua New Guinea which is located in a seismically-active region that experiences frequent large earthquakes generated by crustal and subduction sources. &#160;A suite of ground motion prediction equations (GMPEs) was developed for each source type (crustal, interface and in-slab) using the scaled-backbone approach. &#160;To this end, a ground-motion database consisting of events of 4.0<Mw<8.0 was compiled from available local and regional monitoring stations. &#160;Ground motions were classified based on the source type and converted to a common reference site condition. &#160;The site-corrected motions were compared against alternative GMPEs to examine residual trends between observed and predicted amplitudes.&#160; A backbone model that represents the best estimate of the median ground motions for each source type was selected. &#160;The backbone models were then adjusted to the median of the ground motions observed at the study site.</p><p>The epistemic uncertainty in median predictions was modeled using a logic-tree approach, where the distribution of potential median predictions is approximated by a lower, central and upper model. &#160;The central model is represented by the site-adjusted backbone model; it was scaled to define the lower and upper branches. &#160;The scaling factor was determined considering: (i) the standard deviation in median prediction of alternative GMPEs; and (ii) epistemic uncertainties recommended in other studies. &#160;The available data were insufficient to model aleatory variability with confidence; therefore, the standard deviation of observed motions in data-rich regions is used for guidance. &#160;Two alternative aleatory variability models (ergodic and single-station sigma) adopted from other studies are recommended.</p>
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