Monte Carlo algorithms for evaluating Sobol' sensitivity indices

DOI10.1016/j.matcom.2009.09.005zbMath1207.65004OpenAlexW1983024074MaRDI QIDQ622172

Sumit K. Garg

Publication date: 31 January 2011

Published in: Mathematics and Computers in Simulation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.matcom.2009.09.005

zbMATH Keywords

sensitivity analysisnumerical experimentsmultidimensional numerical integrationglobal sensitivity indicesadaptive Monte Carlo algorithm

Mathematics Subject Classification ID

Monte Carlo methods (65C05)

Related Items

Further results on orthogonal arrays for the estimation of global sensitivity indices based on alias matrix, Advanced Monte Carlo Methods to Neural Networks, An Efficient Adaptive Monte Carlo Approach for Multidimensional Quantum Mechanics, An Overview of Lattice and Adaptive Approaches for Multidimensional Integrals, Advanced Quasi-Monte Carlo Algorithms for Multidimensional Integrals in Air Pollution Modelling, Sensitivity Studies of an Air Pollution Model by Using Efficient Stochastic Algorithms for Multidimensional Numerical Integration, Efficient Stochastic Approaches for Multidimensional Integrals in Bayesian Statistics, Nonintrusive Polynomial Chaos Expansions for Sensitivity Analysis in Stochastic Differential Equations

Uses Software

• TOMS659
• TESTPACK

Cites Work

• Making best use of model evaluations to compute sensitivity indices
• Parallel globally adaptive algorithms for multi-dimensional integration
• Computational and numerical challenges in environmental modelling
• Tensor Analysis of ANOVA Decomposition
• Exact Error Estimates and Optimal Randomized Algorithms for Integration
• Algorithm 659
• Discrépance de suites associées à un système de numération (en dimension s)
• Mersenne twister
• An adaptive algorithm for the approximate calculation of multiple integrals
• Weighted Average Importance Sampling and Defensive Mixture Distributions
• A Class of Statistics with Asymptotically Normal Distribution
• Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates
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