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

Jean-Yves Tissot (1, 2) , Clémentine Prieur (1, 2)

1 GdR MASCOT-NUM - Méthodes d'Analyse Stochastique des Codes et Traitements Numériques
2 MOISE - Modelling, Observations, Identification for Environmental Sciences

In this paper, we present a general way to correct a positive bias which occurs in all the estimators in random balance design method (RBD) and in its hybrid version, RBD-FAST. Both these techniques derive from Fourier amplitude sensitivity test (FAST) and, as a consequence, are faced with most of its inherent issues. And up to now, one of these, the well-known problem of interferences, has always been ignored in RBD. After presenting in which way interferences lead to a positive bias in the estimator of first-order sensitivity indices in RBD, we explain how to overcome this issue. We then extend the bias correction method to the estimation of sensitivity indices of any order in RBD-FAST. We also give an economical strategy to estimate all the first-order and second-order sensitivity indices using RBD-FAST.

Mots clés: Bias correction; RBD-FAST; Random balance design; Sensitivity indices; Global sensitivity analysis

Domaines: Mathématiques générales [math.GM]; Applications [stat.AP]

Jean-Yves Tissot, Clémentine Prieur. Bias correction for the estimation of sensitivity indices based on random balance designs. Reliability Engineering and System Safety, 2012, 107, pp.205-213. ⟨10.1016/j.ress.2012.06.010⟩. ⟨hal-00507526v2⟩