1,853 research outputs found
Global sensitivity analysis of computer models with functional inputs
Global sensitivity analysis is used to quantify the influence of uncertain
input parameters on the response variability of a numerical model. The common
quantitative methods are applicable to computer codes with scalar input
variables. This paper aims to illustrate different variance-based sensitivity
analysis techniques, based on the so-called Sobol indices, when some input
variables are functional, such as stochastic processes or random spatial
fields. In this work, we focus on large cpu time computer codes which need a
preliminary meta-modeling step before performing the sensitivity analysis. We
propose the use of the joint modeling approach, i.e., modeling simultaneously
the mean and the dispersion of the code outputs using two interlinked
Generalized Linear Models (GLM) or Generalized Additive Models (GAM). The
``mean'' model allows to estimate the sensitivity indices of each scalar input
variables, while the ``dispersion'' model allows to derive the total
sensitivity index of the functional input variables. The proposed approach is
compared to some classical SA methodologies on an analytical function. Lastly,
the proposed methodology is applied to a concrete industrial computer code that
simulates the nuclear fuel irradiation
Statistical Analysis and Parameter Selection for Mapper
In this article, we study the question of the statistical convergence of the
1-dimensional Mapper to its continuous analogue, the Reeb graph. We show that
the Mapper is an optimal estimator of the Reeb graph, which gives, as a
byproduct, a method to automatically tune its parameters and compute confidence
regions on its topological features, such as its loops and flares. This allows
to circumvent the issue of testing a large grid of parameters and keeping the
most stable ones in the brute-force setting, which is widely used in
visualization, clustering and feature selection with the Mapper.Comment: Minor modification
Global Sensitivity Analysis of Stochastic Computer Models with joint metamodels
The global sensitivity analysis method, used to quantify the influence of
uncertain input variables on the response variability of a numerical model, is
applicable to deterministic computer code (for which the same set of input
variables gives always the same output value). This paper proposes a global
sensitivity analysis methodology for stochastic computer code (having a
variability induced by some uncontrollable variables). The framework of the
joint modeling of the mean and dispersion of heteroscedastic data is used. To
deal with the complexity of computer experiment outputs, non parametric joint
models (based on Generalized Additive Models and Gaussian processes) are
discussed. The relevance of these new models is analyzed in terms of the
obtained variance-based sensitivity indices with two case studies. Results show
that the joint modeling approach leads accurate sensitivity index estimations
even when clear heteroscedasticity is present
Some conjectures on the two main power indices
The purpose of this paper is to present a structural specification of the Shapley- Shubik and Banzhaf power indices in a weighted voting rule. We compare them in term of the cardinality of the sets of power vectors (PV). This is done in different situations where the quota or the number of seats are fixed or not.Shapley-Shubik, Banzhaf, power index, power vectors.
The role of relational competence in the health care sector
International audienceThe role of entrepreneurs is highly regarded in our societies. It is widely recognized that their roles are not limited to the private sector, but can affect all sectors of the economy. In view of this, we focus on entrepreneurs acting in the healthcare sector. We concentrate more particularly on these entrepreneurs' specific competences. We propose to conceptualise the concept of relational competence, defined as the act of building and structuring relationships in order to adapt and innovate in a given environment. The aim of this exploratory study is to better understand why this type of competence is expected on the construction site of a new hospital in France
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