Bias correction for the estimation of sensitivity indices based on random balance designs

This paper deals with the random balance design method (RBD) and its hybrid approach, RBD-FAST. Both these global sensitivity analysis methods originate from Fourier amplitude sensitivity test (FAST) and consequently face the main problems inherent to discrete harmonic analysis. We present here a general way to correct a bias which occurs when estimating sensitivity indices (SIs) of any order – except total SI of single factor or group of factors – by the random balance design method (RBD) and its hybrid version, RBD-FAST. In the RBD case, this positive bias has been recently identified in a paper by Xu and Gertner [1]. Following their work, we propose a bias correction method for first-order SIs estimates in RBD. We then extend the correction method to the SIs of any order in RBD-FAST. At last, we suggest an efficient strategy to estimate all the first- and second-order SIs using RBD-FAST.

► We provide a bias correction method for the global sensitivity analysis methods: RBD and RBD-FAST.
► In RBD, first-order sensitivity estimates are corrected.
► In RBD-FAST, sensitivity indices of any order and closed sensitivity indices are corrected.
► We propose an efficient strategy to estimate all the first- and second-order indices of a model.