Sequential design for achieving estimated accuracy of global sensitivities

Global sensitivity analysis provides information on the relative importance of the input variables for simulator functions used in computer experiments. It is more conclusive than screening methods for determining if a variable is influential, especially if a variable's influence is derived from its interactions with other variables. In this paper, we develop a method for providing global sensitivities with estimated accuracy. A treed Gaussian process serves as a statistical emulator of the black box function. A sequential experimental design makes effective and efficient use of simulator evaluations by adaptively sampling points that are expected to provide the maximum improvement to the emulator model. The method accounts for both sampling error and emulator error. Copyright © 2014 John Wiley & Sons, Ltd.