Morris method
Morris Method is the screening method proposed by Morris (1991) and recently improved by Campolongo et al. (2003) is very effective to screen a subset of few important input factors among a large number contained in a model. In this work the enhanced Morris method is first confronted with the variance based methods and then employed to assess the sensitivity of a financial model for option pricing.
A sensitivity analysis method widely used to screen factors in models of large dimensionality is the design proposed by Morris [1]. The Morris method deals efficiently with models containing hundreds of input factors without relying on strict assumptions about the model, such as for instance additivity or monotonicity of the model input-output relationship.The Morris method is simple to understand and implement, and its results are easily interpreted. Furthermore it is economic in the sense that it requires a number of model evaluations that is linear in the number of model factors. The method can be regarded as global as the final measure is obtained by averaging a number of local measures (the elementary effects), computed at different points of the input space.[2]
References
- Morris, M.D. (1991). "Factorial Sampling Plans for Preliminary Computational Experiments,Technometrics" (PDF). http://www.jstor.org/. 33: 161–174.
{{cite journal}}: External link in|journal= - Campolongo,Cariboni,Saltelli, F., J.and A. (2003). "Sensitivity analysis: the Morris method versus the variance based measures. Submitted to Technometrics" (PDF). http://www.jstor.org/.
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