Simulation-based sensitivity analysis: Methods and software tools

Abstract

The topic of the paper is simulation-based sensitivity analysis with emphasize on the use of the small-sample Latin Hypercube Sampling simulation method. Three approaches are described in the paper: Spearman’s rank-order correlation, covariance-based sensitivity analysis and input perturbation-based sensitivity analysis. Software tools are briefly described, especially SEAN software as an effective sensitivity analysis environment developed to simplify sensitivity analysis of a user-defined numerical model. An example application is presented.The topic of the paper is simulation-based sensitivity analysis with emphasize on the use of the small-sample Latin Hypercube Sampling simulation method. Three approaches are described in the paper: Spearman’s rank-order correlation, covariance-based sensitivity analysis and input perturbation-based sensitivity analysis. Software tools are briefly described, especially SEAN software as an effective sensitivity analysis environment developed to simplify sensitivity analysis of a user-defined numerical model. An example application is presented.