Statistical methods for sensitivity and performance analysis in computer experiments

We describe statistical methods for sensitivity and performance analysis of complex computer simulation experiments. Graphical methods, such as trellis plots, are suggested for exploratory analysis of individual or aggregate performance metrics, conditional on different experiment inputs. More formal statistical methods, such as analysis of variance based methods and regression tree analysis, are used to determine variables having substantive influence on the experimental results and to investigate the structure of the underlying relationship between inputs and outputs. The methods are discussed in relation to a supply chain model of the textile manufacturing process having many possible input and output variables of interest and for a computer model used to describe the flow of material in an ecosystem