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Metamodels and the Bootstrap for Input Model Uncertainty Analysis

Thursday 8th September 2011 - 11:30 to 12:00
INI Seminar Room 1
Session Title: 
Metamodeling and stochastic simulation II
Session Chair: 
J. Kleinjnen
The distribution of simulation output statistics includes variation form the finiteness of samples used to construct input probability models. Metamodels and bootstrapping provide a way to characterize this error. The metamodel-fiting experiment benefits from a sequential design strategy. We describe the elements of such a strategy, and show how they impact performance.
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Presentation Material: 
University of Cambridge Research Councils UK
    Clay Mathematics Institute London Mathematical Society NM Rothschild and Sons