TY - JOUR
T1 - Non-parametric estimation of conditional moments for sensitivity analysis
AU - Ratto, M.
AU - Pagano, A.
AU - Young, P. C.
PY - 2009/2
Y1 - 2009/2
N2 - In this paper, we consider the non-parametric estimation of conditional moments, which is useful for applications in global sensitivity analysis (GSA) and in the more general emulation framework. The estimation is based on the state-dependent parameter (SDP) estimation approach and allows for the estimation of conditional moments of order larger than unity. This allows one to identify a wider spectrum of parameter sensitivities with respect to the variance-based main effects, like shifts in the variance, skewness or kurtosis of the model output, so adding valuable information for the analyst, at a small computational cost.
AB - In this paper, we consider the non-parametric estimation of conditional moments, which is useful for applications in global sensitivity analysis (GSA) and in the more general emulation framework. The estimation is based on the state-dependent parameter (SDP) estimation approach and allows for the estimation of conditional moments of order larger than unity. This allows one to identify a wider spectrum of parameter sensitivities with respect to the variance-based main effects, like shifts in the variance, skewness or kurtosis of the model output, so adding valuable information for the analyst, at a small computational cost.
KW - Conditional moments
KW - Non-parametric methods
KW - Sensitivity analysis
KW - State-dependent parameter models
UR - http://www.scopus.com/inward/record.url?scp=54049155765&partnerID=8YFLogxK
U2 - 10.1016/j.ress.2008.02.023
DO - 10.1016/j.ress.2008.02.023
M3 - Article
SN - 0951-8320
VL - 94
SP - 237
EP - 243
JO - Reliability Engineering and System Safety
JF - Reliability Engineering and System Safety
IS - 2
ER -