Conclusions derived from world models have little value if they do no include an estimate of the uncertainty associated with the outputs. This paper describes the System Analysis Research Unit World Model and gives an account of the application of Monte Carlo techniques to testing the model. Samples of uncertain data encoded in probability densities are used as input for model runs. The model output is analysed statistically and the contribution to total uncertainty by the variance of the inputs is determined. The output is also to be additive over a limited range. Due to the strong negative feedback loops in the model, the model usually attenuates any variation in inputs. The cost of Monte Carlo methods is justified by the quality of the results obtained.

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Date created

• 1976

Type

• Document

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• Processing documentation available at: https://wiki.albany.edu/display/SCA/Processing+Ingested+Digital+Files

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• Creative Commons BY-NC-ND Attribution-NonCommercial-NoDerivs 4.0 International

  
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dbb17ec8affa7ecbcd419a760cb61093

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Collection

System Dynamic Society Records

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Collecting area

• This collection is part of the University Archives