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Sensitivity Analysis
Abstract
Sensitivity analysis is a mathematical technique for investigating the effects of inaccuracies in the parameters of a mathematical model. It analyses how variation in the output of a model (numerical or otherwise) can be apportioned qualitatively or quantitatively to different sources of data. Sensitivity analysis is an important statistical validation technique in Bayesian Modelling. It is used to ascertain how a given model output depends upon or determines its input parameters. It often carried out to ensure the quality and accuracy of a model and a way of checking the robustness and reliability of assumptions built into a model. This Chapter offers an accessible introduction to sensitivity analysis of Bayesian models. The Chapter should have been a section in Chapter 12 and presented before the scenarios sections in Chapter 12. But because sensitivity analysis itself is a complex subject, it was deemed wise to present it as a complete Chapter on its own.
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