Multiple predictor smoothing methods for sensitivity analysis

  title={Multiple predictor smoothing methods for sensitivity analysis},
  author={Curtis B. Storlie and Jon C. Helton},
  journal={Proceedings of the Winter Simulation Conference, 2005.},
  pages={9 pp.-}
The use of multiple predictor smoothing methods in sampling-based sensitivity analyses of complex models is investigated. Specifically, sensitivity analysis procedures based on smoothing methods employing the stepwise application of the following nonparametric regression techniques are described: (i) locally weighted regression (LOESS), (ii) additive models (GAMs), (iii) projection pursuit regression (PP_REG), and (iv) recursive partitioning regression (RP_REG). The indicated procedures are… CONTINUE READING