TY  - JOUR
A1  - Scherbaum, Frank
A1  - Delavaud, Elise
A1  - Riggelsen, Carsten
T1  - Model selection in seismic hazard analysis : an information-theoretic perspective
N2  - Although the methodological framework of probabilistic seismic hazard analysis is well established, the selection of models to predict the ground motion at the sites of interest remains a major challenge. Information theory provides a powerful theoretical framework that can guide this selection process in a consistent way. From an information- theoretic perspective, the appropriateness of models can be expressed in terms of their relative information loss (Kullback-Leibler distance) and hence in physically meaningful units (bits). In contrast to hypothesis testing, information-theoretic model selection does not require ad hoc decisions regarding significance levels nor does it require the models to be mutually exclusive and collectively exhaustive. The key ingredient, the Kullback-Leibler distance, can be estimated from the statistical expectation of log-likelihoods of observations for the models under consideration. In the present study, data-driven ground-motion model selection based on Kullback-Leibler-distance differences is illustrated for a set of simulated observations of response spectra and macroseismic intensities. Information theory allows for a unified treatment of both quantities. The application of Kullback-Leibler-distance based model selection to real data using the model generating data set for the Abrahamson and Silva (1997) ground-motion model demonstrates the superior performance of the information-theoretic perspective in comparison to earlier attempts at data- driven model selection (e.g., Scherbaum et al., 2004).
Y1  - 2009
UR  - https://publishup.uni-potsdam.de/frontdoor/index/index/docId/31893
UR  - http://bssa.geoscienceworld.org/
SN  - 0037-1106
ER  -