This dramatically clarifies the workings of a model. Model structure is linked among views using Shadow Variables. Monte Carlo Sensitivity Simulations Sensitivity testing involves changing your assumptions about the value of inputs to the model while performing multiple simulations, then examining the uncertainty in selected output variables. Monte Carlo simulations, also known as Multivariate Sensitivity Simulations, automates sensitivity testing. Distributions for input variables include random uniform, normal, triangular, Poisson, Weibull and others.
Output is displayed as graphs with confidence bounds.
These are similar to the Venapp flight simulators available only in Vensim DSS, but have simpler functionality. Vensim PLE Plus can be purchased by credit card on our secure sever.