We define and study a generalization of Sobol sensitivity indices for the case of a vector output. To cite this article: F. Gamboa, A. Janon, T. Klein, A. Lagnoux, C. R. Acad. Sci. Paris, Ser. xx xxx (2013).

Monte Carlo sampling has become a major vehicle for approximate inference in Bayesian networks. In this paper, we investigate a fam­ ily of related simulation approaches, known collectively as quasi-Monte Carlo methods based on deterministic low-discrepancy se­ quences. We first outline several theoreti­ cal aspects of deterministic low-discrepancy sequences, show three examples of such se­ que...

Sobol, and seminar participants at the September 1999 Brookings Panel for helpful comments. Scott Nicholson has provided excellent research assistance. The views expressed here are those of the authors, and do not necessarily reflect those of the Federal Reserve Bank of New York, the Federal Reserve System, or any other institution with which the authors are affiliated.

An adaptive Monte Carlo strategy for computing global Sobol ́ sensitivity indices has been presented and discussed. The experimental scheme including an approximation tool, variance-based approaches for sensitivity analysis and Monte Carlo technique for multidimensional integration has been described and studied.

Concepts and implementation of the Cuba library for multidimensional numerical integration are elucidated. 1. Overview Cuba [1] is a library for multidimensional numerical integration. It features four integration algorithms with interfaces for Fortran, C/C++, and Mathematica. All four can integrate vector integrands and their invocation is quite similar to make it easy to switch routines for c...