PREP, Input Preparation for Monte-Carlo Program SPOP. SPOP-4, Uncertainty and Sensitivity Analysis Monte-Carlo Program with Input from PREP

1 - Description of program or function - The PREP program (data PRE Processing Unit) prepares samples for a Monte Carlo simulation using the distribution functions of the input variables. Any degree of correlation among the variables can be requested in the input. The SPOP program (Statistics Post Processing Unit) is used for performing uncertainty analysis and sensitivity analysis on the output of the simulation runs. SPOP provides for each output variable - a histogram and cumulative distribution; - confidence bounds on the cumulative distribution; - mean and confidence bounds on the mean; - estimate of the sensitivity of each output variable to card input variable. 2 - Method of solution: The sampling in PREP can be carried out purely random or by using the Latin Hypercube Technique (LHS). The technique of Iman and Conover is used to eliminate spurious correlations or to impose pre-specified correlations. The prepared samples are stored on an external file for further use. SPOP uses Kolmogorov statistics for estimating confidence bounds on the cumulative distribution and the Tschebyscheff's theorem for the mean end confidence bounds on the mean. The estimation of sensitivities are carried out using: - Smirnov's test; - Spearman's test; - Cramer test; - Two sample T test; - Kendall's test; - Mann-Whitney's test; - Klotz's test; - Sum of squared ranks' test