wd41-thesis
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Contents:

  • Quantifying Uncertainty of Computer Model: Forward and Backward
  • Reflood
  • Sensitivity Analysis: Understanding Model Input/Output Relationship under Uncertainty
  • Gaussian Process Metamodeling: Emulating Code Input/Output for Faster Evaluation
  • Bayesian Calibration of Computer Model: Connecting Uncertain Model and Uncertain Data
    • Statistical Formulation of Model Calibration Problem
    • Model Discrepancy and Its Modeling
    • Modular Bayesian Approach
    • Posterior Distribution Approximation: Markov Chain Monte Carlo Simulation
    • Identifiability Issue and Its Solution
    • Calibration of a Simple Problem
    • Calibration of TRACE Reflood Model using One Model Response
    • Calibration of TRACE Reflood Model using Multiple Model Responses
    • Chapter Summary
  • Bibliography
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  • Bayesian Calibration of Computer Model: Connecting Uncertain Model and Uncertain Data
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Bayesian Calibration of Computer Model: Connecting Uncertain Model and Uncertain DataΒΆ

Bayesian Calibration:

  • Statistical Formulation of Model Calibration Problem
  • Model Discrepancy and Its Modeling
  • Modular Bayesian Approach
  • Posterior Distribution Approximation: Markov Chain Monte Carlo Simulation
  • Identifiability Issue and Its Solution
  • Calibration of a Simple Problem
  • Calibration of TRACE Reflood Model using One Model Response
  • Calibration of TRACE Reflood Model using Multiple Model Responses
  • Chapter Summary
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© Copyright 2017, Damar Wicaksono. Revision 447750c0.

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