Maximum likelihood Bayesian averaging of spatial variability models in unsaturated fractured tuff

@inproceedings{Ye2004MaximumLB,
  title={Maximum likelihood Bayesian averaging of spatial variability models in unsaturated fractured tuff},
  author={Ming Qiang Ye and Shlomo P. Neuman and Philip D. Meyer},
  year={2004}
}
[1] Hydrologic analyses typically rely on a single conceptual-mathematical model. Yet hydrologic environments are open and complex, rendering them prone to multiple interpretations and mathematical descriptions. Adopting only one of these may lead to statistical bias and underestimation of uncertainty. Bayesian model averaging (BMA) [Hoeting et al., 1999] provides an optimal way to combine the predictions of several competing models and to assess their joint predictive uncertainty. However, it… CONTINUE READING
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