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Nonparametric Stochastic Subspaces via the Bootstrap Method for Characterizing Model Error
and-sciencecomputational-engineeringcomputational-physicsdata-analysisfinancemethodologystatistics-and-probability
Reliable forward uncertainty quantification in engineering requires methods that account for aleatory and epistemic uncertainties. In many applications, epistemic effects arising from uncertain parameters and model form dominate prediction error and strongly influence engineering decisions. Because
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