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Moment Independent Importance Measures: New Results and Analytical Test Cases
Author(s) -
Borgonovo Emanuele,
Castaings William,
Tarantola Stefano
Publication year - 2011
Publication title -
risk analysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.972
H-Index - 130
eISSN - 1539-6924
pISSN - 0272-4332
DOI - 10.1111/j.1539-6924.2010.01519.x
Subject(s) - sensitivity (control systems) , moment (physics) , convergence (economics) , test (biology) , sample (material) , computer science , mathematics , econometrics , statistics , engineering , physics , paleontology , classical mechanics , electronic engineering , economics , economic growth , thermodynamics , biology
Moment independent methods for the sensitivity analysis of model output are attracting growing attention among both academics and practitioners. However, the lack of benchmarks against which to compare numerical strategies forces one to rely on ad hoc experiments in estimating the sensitivity measures. This article introduces a methodology that allows one to obtain moment independent sensitivity measures analytically. We illustrate the procedure by implementing four test cases with different model structures and model input distributions. Numerical experiments are performed at increasing sample size to check convergence of the sensitivity estimates to the analytical values.