Identifying important factors in deterministic investment problems using design of experiments

For large investment projects sensitivity analysis is an important tool to determine which factors need further analysis and/or can jeopardize the future of a project. In practice reliable information on the joint probability distribution of factors affecting the investment is mostly lacking, so a stochastic analysis is not possible. This paper analyzes how and to what extend statistical design of experiments in combination with regression meta modeling can be helpful in finding important factors in deterministic models. Information that is useful to decision makers.