A new algorithm for variance based importance analysis of models with correlated inputs
Abstract
Importance analysis is aimed at finding the contributions of the inputs to the output uncertainty. For structural models involving correlated input variables, the variance contribution by an individual input variable is decomposed into correlated contribution and uncorrelated contribution in this study. Based on point estimate, this work proposes a new algorithm to conduct variance based importance analysis for correlated input variables....
Paper Details
Title
A new algorithm for variance based importance analysis of models with correlated inputs
Published Date
Feb 1, 2013
Volume
37
Issue
3
Pages
864 - 875
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