Probabilistic Sensitivity Analysis of Complex Models: A Bayesian Approach

University of Sheffield

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Abstract

Summary In many areas of science and technology, mathematical models are built to simulate complex real world phenomena. Such models are typically implemented in large computer programs and are also very complex, such that the way that the model responds to changes in its inputs is not transparent. Sensitivity analysis is concerned with understanding how changes in the model inputs influence the outputs. This may be motivated simply by a wish to understand the implications of a complex model but often arises because there is uncertainty about the true values of the inputs that should be used for a particular application. A broad range of measures have been advocated in the literature to quantify and describe…

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Topics & keywords

Keywords
  • Sensitivity (control systems)
  • Computer science
  • Bayesian probability
  • Probabilistic logic
  • Range (aeronautics)
  • Set (abstract data type)
  • Sensitivity analysis
  • Monte Carlo method
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