Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Derivative-based global sensitivity measures: general links with Sobol'
  indices and numerical tests   The estimation of variance-based importance measures (called Sobol' indices)
of the input variables of a numerical model can require a large number of model
evaluations. It turns to be unacceptable for high-dimensional model involving a
large number of input variables (typically more than ten). Recently, Sobol and
Kucherenko have proposed the Derivative-based Global Sensitivity Measures
(DGSM), defined as the integral of the squared derivatives of the model output,
showing that it can help to solve the problem of dimensionality in some cases.
We provide a general inequality link between DGSM and total Sobol' indices for
input variables belonging to the class of Boltzmann probability measures, thus
extending the previous results of Sobol and Kucherenko for uniform and normal
measures. The special case of log-concave measures is also described. This link
provides a DGSM-based maximal bound for the total Sobol indices. Numerical
tests show the performance of the bound and its usefulness in practice.

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The categories of this paper are: gr-qc
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The categories of this paper are: chem-ph
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The categories of this paper are: hep-ex
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The categories of this paper are: adap-org
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The categories of this paper are: bayes-an
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The categories of this paper are: hep-lat
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The categories of this paper are: nucl-th
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The categories of this paper are: patt-sol
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The categories of this paper are: dg-ga
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The categories of this paper are: hep-th
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The categories of this paper are: q-alg
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The categories of this paper are: cmp-lg
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The categories of this paper are: supr-con
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The categories of this paper are: solv-int
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The categories of this paper are: plasm-ph
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The categories of this paper are: math-ph